Models of Corrections Essay - 1250 Words

This essay provides answers to the following prompts: 1. What is the community model of corrections? 2. What is the crime control model of corrections? 3. What are the differences between prisons and jails? 4. What is your opinion about the constitutional rights of prisoners? 1. What is the community model of corrections? This model of corrections main purpose was to reintroducing the offenders in to the community. This Program was invented to help offenders in the transition from jail to the community, aid in the processes of finding jobs and stay connected to their families and the community. The needs of these individuals are difficult: the frequency of substance abuse, mental illness, unemployment, and homelessness is†¦show more content†¦Model corrections believe that jail does not rehabilitate offenders in the contraire they often do the opposite, perpetuating the same behavior that led to the offender’s incarceration in the first place. 2. What is the crime control model of corrections? This control model of corrections is based on the sole believe that criminal behavior, can somehow be control by harsh punishments or jail. Crime control model of corrections is more punitive and makes greater use of imprisonment, particularly for violent offenders and career criminals. This model of corrections mandates longer sentences, mandatory punishments, and strict regulation of offenders in probation and parole. Public safety and punishment through incapacitation, deterrence, and retribution: determinate sentencing; sentencing guidelines; increased use of incarceration; mandatory incarceration laws; abolish parole is the main purpose of this model corrections. The result of these tough policies is accredited with the massive record number of people incarcerated, the greater amount of time being served, the vast number of parolees returning to prison, and the increase in the probation population. Numerous advocates accredit the fall of crime rates to the crime control policies. However, others question if the crime control policies have actually made a difference. Crime control corrections are a set of beliefsShow MoreRelatedModels of Corrections Essay1644 Words   |  7 Pagesthe system of corrections in America. Once a new idea goes sour, a new one replaces it. Prisons shifted their focus from the punishment of offenders to the rehabilitation of offenders, then to the reentry into society, and back to incarceration. As times and the needs of the criminal justice system changed, new prison models were organized in hopes of lowering the crime rates in America. The three major models of prisons that were developed were the medical, model, the community model, and the crimeRead MoreEssay on Models of Corrections1625 Words   |  7 Pagesthe system of corrections in America. Once a new idea goes sour, a new one replaces it. Prisons shifted their focus from the punishment of offenders to the rehabilitation of offenders, then to the reentry into society, and back to incarceration. As times and the needs of the criminal justice system changed, new prison models were organized in hopes of lowering the crime rates in America. The three major models of prisons that were developed were the medical, model, the community model, and the crimeRead MoreThe Effect Of Monetary Policy On Determination Of Coal Prices1013 Words   |  5 Pagesvariables. Since the Johansen method is sensitive to changes in lag structure, the lag length for the model is carefully selected using likelihood ratio tests (Doornik and Hendry, 1994). The sequential pairwise equivalence of models from ten- to nine- and eight-lags is rejected at the 10% leve l. However, the hypothesis that there is no significant difference between a seven- and a six-lag model cannot be rejected; hence, a lag length of seven months is used for further analysis. Table 2 reports theRead MoreCorrections: From Rehabilitation to a More Punitive Model Essay1594 Words   |  7 Pagesï » ¿Sameer Noori 24 November 2014 Corrections Paper What changes led corrections away from rehabilitation and toward a more punitive model? Since World War II through the 1970s, many changes occurred in the United States correctional systems. Rehabilitation Model is a treatment program that was designed to reform the inmates. According to www.copower.org, â€Å"This model is similar to the medical model; it regards the person with a disability as in need of services from a rehabilitation professional whoRead MoreForecasting Using Eviews2841 Words   |  12 Pagesused as a leading indicator for the former, to improve on the forecast obtained by the univariate model. Both variables are collected over a time range from January 1985 until and including December 1997, whereas the last year is not used for constructing the optimal forecast, obtained by fitting a model through the data until the end of 1996. This will enable us to forecast the year 1997 using our model, and then comparing it to the actual data. Assuming no large one time shock, meaning that it isRead MoreThe Medical Model, Community Model And The Crime Contro l Model869 Words   |  4 PagesCommunity corrections is continually changing and has been for the past one hundred years. From the early to mid-twentieth century onward it has used three major models, the medical model, community model, and the crime control model. The major turning point for the American community corrections system that led to corrections as we know it today was in 1974 when What Works? - Questions and Answers About Prison Reform by Martinson was published. The system changed practically overnight acrossRead MoreDifferent Kinds Of Punishments And The Corrections System Essay1621 Words   |  7 PagesIn Chapter 10 â€Å"Corrections†, it went over the history, different kinds of punishments, how it affected the inmates, and how the corrections system is now and how different it has changed since the first penitentiary. Being in prison has always been an act of punishment and gives time to the inmate to reflect their actions. Prison isn’t a place to relax and enjoy oneself, an inmate needs to do work or will suffer the consequences. We will look more into the different kinds of systems and how we gotRead MoreThe Incarceration Of The Correctional System910 Words   |  4 Pagesof punishment American reformers argued that they should embrace a more rational and humanistic approach. The Pennsylvania Systems, or penitence model, was based on the ideas of Quakers and there concept of penance. A penitentiary became a place where prisoners could reflect on their offenses and repent and thus undergo reformation. (History Of Corrections In America, 2011). In this system inmates were classified by their offenses, confined separately at night, and worked during the day together inRead MoreElectrical Distribution Feeder Analysis1240 Words   |  5 Pagescalculations. To achieve this goal, the simulation package Matlab was used as the driving force behind the programming and calculating. Discussion 2.1 Individual Segment Modeling To simulate the feeder, the first thing needed is a model of each line segment. To construct this model, code can be written that computes the distances between conductors by using the configurations and conductor values given for each line segment. These results provide the information needed to create the primitive impedanceRead MoreThree Components Of The Criminal Justice System950 Words   |  4 Pagescriminal justice system are the police, courts, and corrections. These components operate independently of one another and maintain different goals, histories, and operating procedures (Neubauer Fradella, 2017). There are two commonly accepted models of the criminal justice system, the crime control model and due process model. These two models vary at the basic level, the crime control model aims to protect society at all costs while the due process model protects the rights of individual citizens (Neubauer

Police Brutality Use Of Excessive And Unnecessary Force...

Police brutality is the use of excessive and unnecessary force by police when dealing with civilians. Police brutality can be present in many ways. The most common form of police brutality is a physical form. Police officers can use nerve gas, batons, pepper spray, and guns in order to physically intimidate or even intentionally hurt civilians. Police brutality can also take the form of false arrests, verbal abuse, psychological intimidation, sexual abuse, police corruption, racial profiling, political repression and the improper use of Tasers. Black people are mostly affected by white cops. Cops are given a lot of scope in performing their obligations. Since they are relied upon to ensure general society and stand up to possibly rough people, they can lawfully utilize physical, and even fatal, power in specific situations. Be that as it may, an officer who uses power when it is not called for, or who utilizes more constraints than is important to perform his or her occupation, m ay go too far into police ruthlessness. Police brutality should be controlled and stopped because its getting out of hand and is killing our African American youth. The term is not a lawful term and the definition is in this manner somewhat delicate; it might be best portrayed by method for instance. A recent case of police brutality occurred on August 9, 2014 in Ferguson, Missouri. Flatow said: This case sparked many other cases similar to Mike Brown’s situation. He was shot and killedShow MoreRelatedPolice Brutality : Use Of Excessive And Unnecessary Force By Police1536 Words   |  7 Pages Police brutality is the use of excessive and unnecessary force by police when dealing with civilians. Police brutality can be present in many ways. The most common form of police brutality is a physical form. Police officers can use nerve gas, batons, pepper spray, and guns in order to physically intimidate or even intentionally hurt civilians. Police brutality can also take the form of false arrests, verbal abuse, psychological intimidation, sexual abuse, police corruption, racial profilingRead MorePolice Brutality And Crime Brutality833 Words   |  4 PagesPolice Brutality Police brutality is defined as the use of excessive or unnecessary force by police when dealing with civilians (What Is Police Brutality?). Recently, there have been a surplus of incidents involving police brutality. Cases like Michael Brown, Eric Garner, and Tamir Rice are examples of police brutality. All three of these victims ended up dead at the hands of police. Statistics show that, just this year alone, 1,013 Americans have been killed by cops (Cop Crisis). Social mediaRead MorePolice Brutality And Police Cruelty1118 Words   |  5 PagesPolice brutality has occurred all across the world and is still a major amongst society and police organization. This brutality arranges from assaults, death as a result, of use of force, harassment, Etc. It takes two forms which is physical brutality which includes assaults, and non-physical brutality which includes use of verbal language. Police officers have been granted the privilege of using â€Å"non-negotiable force† (Bittner 19 70) to control citizens’ behavior and ensure public order. Police useRead MoreRacism And White Privilege Enforcement Essay1292 Words   |  6 PagesPolice officers, who were once referred to as peace keepers, are now more law enforcement officers. Police agencies around the United States seem to be stuck more on quotas and creating revenue for their county or city. Making many officers strive for many unnecessary arrests. Which as a following result has brought up a lot of tension between the police and their citizens. With increasing violence in cities and states; police officers methods have slowly become more aggressive, bringing a rise inRead MoreFree Argumentative Essays : Police Brutality738 Words   |  3 Pages J Free Argumentative Essays: Police Brutality 777 Words 4 Pages Police Brutality Police work is dangerous. Sometimes police put in situations that excessive force is needed. But, because some officers use these extreme measures in situations when it is not, police brutality should be addressed. The use of excessive force may or may not be large problem, but it should be looked into by both the police and the public. For those people who feel racismRead MorePolice Brutality Essay747 Words   |  3 PagesPolice Brutality James Regas December 15, 1996 Outline Thesis: But, because some officers use these extreme measures when it is not needed, police brutality should be addressed. I. Police Brutality A. Racism as a cause II. Police Brutality is not a problem A. Quotes from authorities B. Statistics of Declining Brutality III. Stopping Police Brutality A. Police Stopping themselves Read MoreFreedom Of Speech : The Boston Tea Party Essay1375 Words   |  6 PagesAmerica was a rebel. America rebelled against British forces and made America their own. Freedom of speech was important and America was based on protests. The most famous protest was the Boston Tea Party. However, shortly after gaining independence from England, America started to use their own troops to stop rebellions. In 1792, which was only 5 years after the Bill of Rights was ratified, congress passed the Calling Forth Act. This law gave â€Å"the president the authority to unilaterallyRead MorePolice Brutality And The Police1585 Words   |  7 PagesPolice brutality and office involved shootings have sparked national debate and created a strain between police officers and citizens. Recently, there have been more home videos that display acts of aggression by police officers. These police officers often use excessive forces or a condescending tone towards people of color which is why there needs to be a better way to mend police and civilian relationship. People should be able to trust the police in their communities rather than fear them. PoliceRead MorePolice bruality essay for college class i guess1365 Words   |  6 PagesPolice Brutality Police brutality occurs daily across America. Police brutality can come in various forms, counting lethal and nonlethal force. Comprehending the exact commonness of police brutality is complex, because of the inconsistency in describing police brutality. The trouble in differentiating among justified and unjustified force. Police interactions often can be misconstrued, or sometimes turned around against an officer. Questionable behavior and complaints against officers can be filedRead MorePolice Brutality Based On Racial Profiling1682 Words   |  7 Pagesothers; violence and brutality against innocent citizens is the key to getting the job done. For years, minorities have fallen victim to police brutality based on racial profiling, stereotypes and other unjustifiable reasons that has cost several innocent lives. The involvement of officers in police brutality against minority social groups causes tainted and negative views on policing and their overall duty to protect, when they are ultimately the aggressors in this case. Police brutality is a violent incident

Enneagram Paper free essay sample

I have encountered and interacted with numerous professors. Like any other profession or industry, every one operates in an individual manner and takes a unique approach to how they interact with peers and subordinates. Every professor has their own teaching style and way they feel they should communicate to students. Since learning of the Enneagram and the different personalities and character traits we all possess, I can now see the differences in professors I have dealt with. The Enneagram has introduced me to the variety of personality types and the ways each do business in regards to communicating and interacting with other personality types. In the following, I will describe four professors and their personality types, discussing interaction and communication with each. In the winter session I had a public speaking class with a professor by the name of Suzy Ismail. Her personality type is that of the Helper, or number two. As I have learned in class and reading, a Helper is generous and they support and empower others. Twos are motivated by the need to feel appreciated and they like to express their positive thoughts to others. Helpers tend to offer compliments and are naturally wired to make people feel welcome and appreciated. One of the greatest traits of twos is their heartfelt desire to work with people and assist others in achieving. Helpers take pride in helping others as they have a need to feel needed. By serving others, they are able to fulfill a need and craving that only helping others provides for them. Twos have an encouraging leadership style and approach. They are known as the cheerleaders of people and manage by portraying enthusiasm and pride. Twos take pride in making a difference in people’s lives and enjoy being acknowledged for doing so. A negative aspect of twos is they may want to change or improve other people for the sake of their own satisfaction. The teacher/student relationship was a positive and beneficial experience for me and I also believe for Professor Ismail. We both have different personality types and I feel this led to my success in the class. I am a nine and I definitely tend to try to keep the peace and an even keel. In this class, I had to speak in front of the class which I felt uncomfortable doing. Professor Ismail was able to help me overcome this fear and create an improved public speaker out of me. She recognized that I was improving and as a two, this was able to satisfy her desire to support and empower others. We were both different in how we approached public speaking; her desire to change/turn me into a proficient speaker did at times make me feel uncomfortable. She had faith in me that I could be a good speaker while I did not have this same outlook. Her persistence and constantly making us speak, sometimes unexpected, led to my discomfort. Looking back now, I appreciate her method and at the end of the semester, I honestly felt like an improved speaker. She possessed strengths such as making me feel like I can accomplish whatever I wanted in the class, making known her desire to help, praise upon doing well, and nurturing me into an improved speaker. Our communication was positive as she was able to effectively communicate her intentions and aspirations for the class. I felt very open with her and expressed my concerns and worries to her without fear or trepidation. In my first semester at DeVry, I had the privilege of learning from Professor Bell who teaches an intro to computers class. Now it is easy for me to recognize that he is the Top Dog personality type. He is a former Marine officer and I wonder if that played any role in shaping him into this type. As we have discussed, eights like to be in charge, feel responsible autocratic and blunt. Eights can be demanding, confrontational and reckless in their approach. They like to think of themselves as above others and their motto is my way or the high way, there is no room for bargaining here. I view this type of thinking as tunnel vision, I like to be able to find a common ground with people and this type of thinking usually does not allow this. Eights view the world as a game of power and they long to be the one in charge and in control. They either do not care or recognize that they can be loud, offensive, reckless and out of control in their approach to how they communicate and deal with others. The teacher/student relationship here was not uncomfortable or lacking much. As a nine, the eight personality type is one of my wings and I share some things in common with the Top Dog. Because I share part of his personality, our lines of communication were open and I felt comfortable discussing anything with him. This allowed me to speak with him in regards to both class related topics and topics that were unrelated to class. I felt Professor Bell was sometimes very forward and loud in his methods at times, but after while I was able to enjoy and learn from him. He possesses a take charge attitude and has vast amounts of energy in the classroom. In my opinion, this helped me to learn and I desired to pay more attention to him because he had character and at the same time, knew in depth what he was speaking on. At times, he could be blunt and insensitive with how he spoke; this was not an issue for me but may have been for others in the class. He did have an autocratic approach to the class which I viewed as a strength because some professors are not as straight forward. I feel this approach allowed him to take proper control over the class and allowed him to carry out the lessons as he saw fit. Professor Douglas Hatler is another professor who has instructed me since my arrival at DeVry. He teaches an intro to business course as well as accounting. He is of the Visionary personality type and these are also known as planners and optimists. Sevens pride themselves on innovation, optimism, planning and being a consultant. Professor Hatler is a seven who fits the bill to the fullest; he also works in financing and investing, thus allowing him to truly consult. Sevens are creative, interactive and imaginative, generous and lively. They have a strong desire to be happy and like to be surrounded by the like. Sevens are cautious risk takers and weigh out all possibilities when taking risks. This personality type suffers some downfalls in the form of short attention spans, sometimes over stimulated, opinionated and impulsive. Sevens have an interesting approach to leadership style as they applaud ideas while balancing different styles of management. They love to tell stories and can sometimes fall off track or topic when doing so. My experience with Professor Hatler was not the best or worst I have ever known, but after learning of his type I can see why nines and sevens are not immensely different. I found that he sometimes strayed from relevant course content with a story, he was trying to make it relevant to the to lesson but I feel it was not always so. I as a nine have trouble with sevens because they are sometimes as uncertain as I am. This can create a bump in the road of communication; one indecisive person is bad enough, let alone two. Since he was well educated on the subject and his personality type liked consulting, it was easy for me to learn and remember the material he covered because he was able to keep my ttention most of the time. I felt a strength he possessed was enthusiasm and he is an idealist. As a Nine, I look for and appreciate these type of characteristics that a seven displays. Overall, communication with Professor Hatler was easy and enjoyable. We are of two different personality types but this does not imply we were unable to effectively communicate. Our personality types allowed us to share some things in common such as: We both like to avoid confro ntation, nines appreciate the idealism of a seven and nines are just as easygoing as sevens. Upon completing the course, I had an overall feeling and sense of accomplishment and that the professor and I shared good communication with one another. The last professor I will speak of is a current instructor, Professor Rasaq. He teaches a computer scripting and database course and I have discovered that he is a Nine. I am familiar with this personality style as I myself am of the Nine personality type. Nines are referred to as peacemakers, negotiators and desire to live in harmony. This personality type is all about avoiding conflict and are the most likely to identify with all other Enneagram types. They believe in staying calm, friendly and maintaining peace and prosperity amongst everyone. Nines are understanding, reliable, steadfast and humble. Some less desirable traits are: problems with anger and self resentment on a regular basis, too accommodating, stubborn, defensive, forgetful and unassertive. The teacher/student relationship here is an awkward one due to the fact we are both nines. This proves to be a challenge and presents some issues in the classroom. Professor Rasaq is laid back and wants to maintain a peaceful and amicable relationship with everyone as nines tend to do. I feel his passiveness allows for a lax learning environment has he does not want to offend anyone or demand too much from the students. The professor and I obviously share some things and traits in common but I believe that both of us being nines make for some clashing of differences. Although we have some apparent differences, there are several characteristics we have in common. Such as we are both open to doing what the other wants to do, we understand our laid back style as nines and we are both calm in our actions. Some strengths Professor Rasaq exhibits in the classroom are: Including all students when asking a question of policy change, offering extra time for students having trouble and he shares credit when students help him with an idea. As a student I look for my professors to be of the authoritarian type that set rules and follow through with them. Having an instructor of my personality type lets me down in that regard since nines tend to be negotiators and do not push the envelope. Our similar personality types mean we likely share many of the same traits and approach to the different types of relationships. On this note, our communication with each other has been one of ease. The problem is not what is being communicated, its what is not being communicated. There is an overall lack of communication on the whole with all the students. I think the low sides of the nine personality type sometimes take the lead in his style. I try to communicate with him to the best of my ability and this is the most I can do. I have learned that even when people try their best, sometimes you just have to accept what is and move on. I have learned from this class and writing this paper that the nine personality types are all unique and interesting in their own ways. Dissecting the types and learning about how other types of personalities interact and communicate has been interesting and rewarding. Applying the Enneagram and the thoughts therein to my professors has opened my eyes to see how different people communicate from each of the personality types. This is an extremely useful tool and can be applied to everyday life in all forms of relationships. The knowledge of these personality types can allow growth and better interaction between all nine types. The more we can learn and understand our difference and how to work around those differences, the better off we all will be.

Samuel Becketts In Waiting For Godot Essays - Theatre Of The Absurd

Samuel Beckett's In Waiting For Godot Reading a work of literature often makes a reader experience certain feelings. These feeling differ with the content of the work, and are usually needed to perceive the author's ideas in the work. For example, Samuel Beckett augments a reader's understanding of Waiting For Godot by conveying a mood, (one which the characters in the play experience), to the reader. Similarly, a dominant mood is thrust upon a reader in Beowulf. These moods which are conveyed aid the author in conveying ideas to a reader. In Waiting for Godot, Beckett uses many pauses, silences, and ellipses (three dots (...) used to create a break in speech) to express a feeling of waiting and unsureness. There is a twofold purpose behind this technique. For one, it shows that Vladimir and Estragon, the two main characters who are waiting for Godot, are unsure of why they are waiting for him. This also foreshadows that they will be waiting a very long time. In some cases in literature, an idea can only be conveyed properly if those on the receiving end of the idea are able to experience the feelings that a character is experiencing in the work. For example, in order for a reader to feel how and understand why Vladimir and Estragon feel as though they do while they wait, it is essential for that reader to either understand or experience the same feelings that Vladimir and Estragon are experiencing. Vladimir and Estragon are waiting; waiting for Godot, to be exact; and Beckett wants the reader to feel as if he or she were waiting also. Along with the feeling of waiting that a reader may experience, he or she might also understand how Vladimir and Estragon feel at times: Unsure, not very anxious to move on, and constantly having to wait. A feeling of timelessness is even evoked, allowing almost anyone from nearly any time to understand Vladimir and Estragon's predicament. Many times people may feel overwhelmed by a higher force unalterable to them. This force may control something such as their fate. In the Anglo-Saxon culture, a popular belief was that of fate. The writers of Beowulf may have known that not all people believe in the power of fate. Therefore, to properly convey such an idea as the inevitability of fate in the epic, the writers included events which, when read, are also "experienced" by the reader. For example, the narrator of Beowulf states how fate is not on Beowulf's side. After many years of winning countless battles, Beowulf was killed by a dragon in a fierce fight. While he was fighting, and because the narrator had stated that fate was not on his side, the reader could identify with Beowulf and feel how he may have at the time: Overwhelmed, overpowered, and as if a force greater than he was controlling him (his fate). Moods that are created, such as that of longing or waiting, and fear or inevitability, in Waiting for Godot and Beowulf, respectively, hold a distinct purpose. The moods presented usually serve the purpose of helping the author express more fully an the idea or ideas that he or she wishes to convey. Also, by conveying a universal mood, or one that nearly everyone is able to comprehend and interpret, the work of literature's longevity is augmented. This will further help the reader to interpret the work and understand more fully the moods presented.

Free Essays on Society Acceptance

Society acceptance J. D. Salinger’s The Catcher in the Rye focuses on societies acceptance. Holden Caufield attends Pencey, a prestigious school with very high expectations. At Pencey, Holden is excluded by classmates, and frowned upon by the faculty. He sometimes separates himself from his peer group by not becoming involved in school activities. Although Holden participates on the fencing team as the equipment manager, he makes a point to not fit in by losing the equipment. Holden shows that he does not fit in, and does not want to. At the very beginning of the story Holden is expelled from Pencey for not meeting their academic expectations. As he reflects on his final day at Pencey, he says â€Å"They kicked me out... I was flunking four subjects and was not applying myself at all. They gave me frequent warnings to start applying myself but I didn’t do it.† (4) New York City is where Holden ends up after Pencey. Even in New York, Holden feels singled out and ostracized. In a hotel he was staying at, he ran into a pimp who offered him a prostitute for five dollars. Holden accepts, but the next morning the pimp confronts him and tells him he did not pay enough. After a scuffle, in which Holden is injured he leaves the hotel. He feels as if he cannot go to another hotel for fear the same thing will happen. He says â€Å"I had no place to go. It as only Sunday and I couldn’t go home till Wednesday-or Tuesday at the soonest. And I certainly didn’t feel like going to another hotel and getting my brains beat out† (106-107) This shows how very vulnerable Holden is. He does not want to go back home, because he does not belong there at the moment, so he stays in New York. Holden needs the support of the world around him. He came from a generation that could not find their identity, and a society that left people with so little choice that they became bitter and angry much like Holden. Holden’s lack of guidance by hi... Free Essays on Society Acceptance Free Essays on Society Acceptance Society acceptance J. D. Salinger’s The Catcher in the Rye focuses on societies acceptance. Holden Caufield attends Pencey, a prestigious school with very high expectations. At Pencey, Holden is excluded by classmates, and frowned upon by the faculty. He sometimes separates himself from his peer group by not becoming involved in school activities. Although Holden participates on the fencing team as the equipment manager, he makes a point to not fit in by losing the equipment. Holden shows that he does not fit in, and does not want to. At the very beginning of the story Holden is expelled from Pencey for not meeting their academic expectations. As he reflects on his final day at Pencey, he says â€Å"They kicked me out... I was flunking four subjects and was not applying myself at all. They gave me frequent warnings to start applying myself but I didn’t do it.† (4) New York City is where Holden ends up after Pencey. Even in New York, Holden feels singled out and ostracized. In a hotel he was staying at, he ran into a pimp who offered him a prostitute for five dollars. Holden accepts, but the next morning the pimp confronts him and tells him he did not pay enough. After a scuffle, in which Holden is injured he leaves the hotel. He feels as if he cannot go to another hotel for fear the same thing will happen. He says â€Å"I had no place to go. It as only Sunday and I couldn’t go home till Wednesday-or Tuesday at the soonest. And I certainly didn’t feel like going to another hotel and getting my brains beat out† (106-107) This shows how very vulnerable Holden is. He does not want to go back home, because he does not belong there at the moment, so he stays in New York. Holden needs the support of the world around him. He came from a generation that could not find their identity, and a society that left people with so little choice that they became bitter and angry much like Holden. Holden’s lack of guidance by hi...

Costs and Benefits of US Government Regulations

Costs and Benefits of US Government Regulations Do federal regulations – the often controversial rules enacted by federal agencies to implement and enforce the laws passed by Congress cost taxpayers more than they are worth? Answers to that question can be found in a first-ever draft report on the costs and benefits of federal regulations released in 2004 by the White House Office of Management and Budget (OMB). Indeed, federal regulations often have more impact on the lives of Americans than the laws passed by Congress. Federal regulations far outnumber laws passed by Congress. For example, Congress passed 65 significant bills laws in 2013. By comparison, the federal regulatory agencies typically enact more than 3,500 regulations every year or about nine per day. The Costs of Federal Regulations The added expenses of complying with federal regulations born by business and industries have a significant impact on the U.S. economy. According to the U.S. Chambers of Commerce, complying with federal regulations costs U.S. businesses over $46 billion a year. Of course, businesses pass their costs of complying with federal regulations on to consumers. In 2012, the Chambers of Commerce estimated that the total cost for Americans to comply with federal regulations reached $1.806 trillion, or more than the gross domestic products of Canada or Mexico. At the same time, however, federal regulations have quantifiable benefits to the American people. That’s where the OMB’s analysis comes in. More detailed information helps consumers make intelligent choices on the products they purchase. By that same token, knowing more about the benefits and costs of federal regulations helps policymakers promote smarter regulations, said Dr. John D. Graham, director of the OMB’s Office of Information and Regulatory Affairs. Benefits Far Exceed Costs, Says OMB The OMB’s draft report estimated that major federal regulations provide benefits of from $135 billion to $218 billion annually while costing taxpayers between $38 billion and $44 billion. Federal regulations enforcing the EPAs clean air and water laws accounted for the majority of the regulatory benefits to the public estimated over the last decade. Clean water regulations accounted for benefits of up to $8 billion at a cost of $2.4 to $2.9 billion. Clean air regulations provided up to $163 billion in benefits  while costing taxpayers only about $21 billion. Costs and benefits of some other major federal regulatory programs included: Energy: Energy Efficiency and Renewable EnergyBenefits: $4.7 billionCosts: $2.4 billion Health Human Services: Food and Drug AdministrationBenefits: $2 to $4.5 billionCosts: $482 to $651 million Labor: Occupational Safety and Health Administration (OSHA)Benefits: $1.8 to $4.2 billionCosts: $1 billion National Highway Traffic Safety Administration (NTSHA)Benefits: $4.3 to $7.6 billionCosts: $2.7 to $5.2 billion EPA: Clean Air RegulationsBenefits: $106 to $163 billionCosts: $18.3 to $20.9 billion EPA Clean Water RegulationsBenefits: $891 million to $8.1 billionCosts: $2.4 to $2.9 billion The draft report contains detailed cost and benefit figures on dozens of major federal regulatory programs, as well as the criteria used in making the estimates. OMB Recommends Agencies Consider Costs of Regulations Also in the report, OMB encouraged all federal regulatory agencies to improve their cost-benefit estimation techniques and to carefully consider costs and benefits to taxpayers when creating new rules and regulations. Specifically, OMB called on regulatory agencies to expand use of cost-effectiveness methods as well as benefit-cost methods in regulatory analysis; to report estimates using several discount rates in regulatory analysis; and to employ formal probability analysis of benefits and costs for rules based on uncertain science that will have more than a $1 billion-dollar impact on the economy. Agencies Must Prove Need for New Regulations The report also reminded regulatory agencies they must prove that a need exists for the regulations they create. When creating a new regulation, OMB advised, Each agency shall identify the problem that it intends to address (including, where applicable, the failures of private markets or public institutions that warrant new agency action) as well as assess the significance of that problem. Trump Trims Federal Regulations Since taking office in January 2017, President Donald Trump has carried through on his campaign promise to cut the number of federal regulations. On January 30, 2017, he issued an executive order entitled â€Å"Reducing Regulation and Controlling Regulatory Costs† directing the federal agencies to repeal two existing regulations for every new regulation and to do so in such a way that the total cost of regulations does not increase. According to an update status report on Trump’s order from the OMB, the agencies are far exceeding the two-for-one and regulatory cap requirements, having achieved a 22-1 ratio during the first eight months of FY 2017. Overall, notes the OMB, the agencies had cut 67 regulations while adding only 3 â€Å"significant† ones. By August 2017, Congress had exercised the Congressional Review Act to eliminate 47 regulations issued by President Barack Obama. In addition, the agencies had voluntarily withdrawn over 1,500 of Obama’s regulations that were under consideration but not yet finalized. Under Trump, the agencies have generally been more reluctant to propose new regulations. Finally, to help business and industry deal with existing regulations, Trump issued the Streamlining Permitting and Reducing Regulatory Burdens for Domestic Manufacturing on January 24, 2017. This order directs the agencies to expedite federal environmental review approval of bridge, pipeline, transportation, telecommunications and other infrastructure improvement projects.

Medical microbiology Assignment Example | Topics and Well Written Essays - 2000 words

Medical microbiology - Assignment Example (ii) The most commonly used stain for the gastric biopsy for the detection of H. pylori is the modified giemsa stain. Sections of the biopsy in a patient with gastritis would show epithelial damage and a generalized decrease in the thickness of the mucus layer. Eroded areas of the stomach lining would also show the presence of white blood cells such as lymphocytes and neutrophils. A haematoxylin and eosin stain of a person with chronic gastritis would show polymorphonuclear leucocytes intruding into the lining of the mucus gland. Helicobacter pylori resides deep into the lining of the stomach wall, and as the polymorphonuclear cell cannot easily reach the site of infection, they release superoxide radicals which damages the stomach lining. A methylene blue stain of the section would stain the H. pylori bacteria blue and would present as small curve shaped, spiral bacteria in the mucus lining. (iii) 13C urea breath test is a very accurate, non-invasive, simple test that can produce results within 20 minutes. Helicobacter pylori produces urease enzyme which forms the basis of 13C urea breath test. The patient is given a non-radioactive 13C urea to drink, which is broken down into ammonia and bicarbonate by the urease enzyme in Helicobacter pylori. Bicarbonate ions dissociate into Carbon dioxide and water in the acidic environment of the stomach. The 13C isotope containing carbondioxide is absorbed into the blood stream and taken to the lungs to be expired. Readings are taken of the expired air and the results are sent to the lab for Mass correlation spectrometry to be performed and levels of 13CO2 are determined, which are synonymous with the presence of Helicobacter pylori. (iv) A triple regimen therapy is advised to the patient, which consists of a proton pump inhibitor (e.g. omeprazole) and two antibiotics (e.g. amoxicillin,

Reading summaries Assignment Example | Topics and Well Written Essays - 250 words

Reading summaries - Assignment Example Protest scholars are concerned with restoring injustice. In protesters concept, they look at human rights as the theory that favors the status quo in favor of the oppressed (Dembour 3). However, the disclose scholars believe that human rights exist because everyone talks about them. Human rights according to Beitz, is a communication in the public ethics of world policies. He argues that every individual is the subject of the world concern and that it is everyone’s task to enact these rules (Beitz 1). Universality is a worry of whether all the human rights included can be seen as important by everyone. As such, most people tend to misuse these rules for their selfish reasons. There are different forms of skepticism in which some individuals think that there should be a form of a procedure to implement these human rights. The first skeptic clarifies that the satisfaction of some human rights is not realistic under the current social position of the world (Beitz 3). Finally, there is a skeptical concept that explains that human rights are universal. As such, the rights are relevant and are to be claimed by everyone. Maurice, an author supports the traditional human rights, which includes the political and civil rights. However, he rejects the universal human rights, which are termed as economical and social rights that encompass pensions, holidays, insurance among others. Universality according to Cranston is a right available to everyone at all times. For instance, the right to humane treatment is a perfect example of universality. There is a test for human rights and moral uprightness. Practicability Test, clarifies that it is not a duty for an individual to do what is physically impossible (Maurice and Raphael 50). For instance, if all workers in the world should ask for holiday rights then, it would not be practicable for industries that are establishing. The test of paramount

Google Car Essay Example for Free

Google Car Essay Google Car: In the paper, the point of view will be Google’s. Questions that will be answered in the paper including but not limited to the economical and technical viability for Google to produce Google car in a large scale, reasons that Google will succeed or fail, the best strategy for Google to adopt. For the industry analysis, Porter’s five forces (Appendix 1) will be used to explore the environment of the automobile industry and if Google will be able to enter the industry and produce automobiles on its own. The financials of Google will also be analyzed to prove if it is economically capable of investing enough capitals in the system and manufacturing automobiles. A SWOT analysis and discussion of the competitive advantages of Google will also be included to examine the internal capability of Google. Since the idea of a Google Car was introduced, the reviews have been polarized. here are plenty of positive comments about Google Car. Google’s strong and enormous database, especially data on maps is greatly applauded and trusted to be useful and essential in developing the driverless car. On the other hand, there are skeptics who question Google’s ability to produce the automobiles because car building requires certain expertise that Google does not have. In addition, pressures from automobile manufactures, unions and insurance companies might hinder the certain legislations of manufacturing driverless cars to be approved by Congress. The actions that Google should take to rebut the doubts that public and critics have about the functions, utility, safety, etc. about the car will also suggested in the paper. The most crucial question that the paper will try to answer is what is the optimal strategy that Google should do with Google Car. There are many possible outcomes including allying with an automobile manufacturer, purchasing a manufacturer, selling the technology of its driverless car system to interested manufacturers. All three strategies will be discussed and one final solution will be suggested for Google. Sources: 1. Muller, Joann. â€Å"Will Google Kill The Auto Industry? No, And Heres Why†. Forbes.com, January 25th, 2013. Accessed April 2nd,2013. http://web.ebscohost.com/ehost/detail?sid=00fae55e-c3c5-4b78-bd6e-326f38265257%40sessionmgr10vid=2hid=23bdata=JnNpdGU9ZWhvc3QtbGl2ZQ%3d%3d#db=bthAN=85142822 2. Academic Minds (2012). Automotive Industry Analysis-GM,DaimlerChrysler, Toyota, Ford, Honda. Accessed November 27th, 2012 from: http://academicmind.com/unpublishedpapers/business/management/2004-11-000aaa-automotive-industry-analysis.html 3. IBIS World (2012). IBIS World-Car and Automotive Manaufacturing. Accessed November 26th, 2012. http://clients1.ibisworld.com/reports/us/industry/default.aspx?entid=826 4. Investopedia (2012). The Industry Handbook: Automobiles. Accessed November 26th, 2012. http://www.investopedia.com/features/industryhandbook/automobile.asp#axzz2D0aOFEIL 5. Helft, Miguel, â€Å"Larry Page looks ahead†. Fortune, 00158259, 1/14/2013, Vol. 167, Issue 1. Accessed on March 29th, 2013. http://web.ebscohost.com/ehost/detail?sid=dac8d930-8af3-40fa-91e3-71f73362d61a%40sessionmgr111vid=2hid=121bdata=JnNpdGU9ZWhvc3QtbGl2ZQ%3d%3d#db=bthAN=85623367 6. Brown, Alan S. â€Å"Google’s Autonomous car applies lessons learned from driverless races†. Mechanical Engineering. Feb. 2011. Accessed 29th March,2013 http://web.ebscohost.com/ehost/pdfviewer/pdfviewer?sid=405dc68c-19c8-4554-addd-6e6b7371c8fa%40sessionmgr11vid=6hid=10 7. Higgins, Tim. â€Å"Will driverless cars become the new road rage?† Bloomberg Businessweek. December 1st, 2011. Accessed on 1st April. http://www.businessweek.com/magazine/will-driverless-cars-become-the-new-road-rage-12012011.html 8. Brown, Jerry. â€Å"California legalizes driverless cars† Electronics Weekly. October, 2012. Accessed 1st April. 2013. http://web.ebscohost.com/ehost/detail?sid=405dc68c-19c8-4554-addd-6e6b7371c8fa%40sessionmgr11vid=5hid=10bdata=JnNpdGU9ZWhvc3QtbGl2ZQ%3d%3d#db=bthAN=82337032 9. Knapp, Alex. â€Å"Nevada passes regulations for driverless cars†. February, 2012. Accessed 1st April. 2013 http://web.ebscohost.com/ehost/detail?sid=405dc68c-19c8-4554-addd-6e6b7371c8fa %40sessionmgr11vid=5hid=10bdata=JnNpdGU9ZWhvc3QtbGl2ZQ%3d%3d#db=bthAN=71870057 Appendix 1: Preliminary Industry Analysis A. Competitive dynamics within the industry The automobile manufacturing industry t is often considered as an oligopoly, where there is a medium to high industry concentration and only a handful of key players exist: Toyota, General Motors, Ford Motor, Hyundai-Kia Automotive Group and Honda (IBIS World 2012). â€Å"Automakers compete primarily on the basis of price, fuel economy, reliability, styling and utility† (IBIS World 2012). B. Bargaining power of suppliers Due to the numerous parts that are required to produce an automobile, there are many suppliers in the supplying business and they are quite segmented, thus the bargaining power of suppliers in the automobile industry is extremely low. C. Bargaining power of customers In the automobile industry, customers hold medium amount of power. Consumers account for a significant or almost all of the industry’s outputs and revenues, and there is low cost involved in switching, the companies have to accommodate their tastes and needs. There are numerous factors that can alter their buying decision: brands, appearances, quality, functions, environmental effects and prices. Due to different demographics of the consumers, the manufacturers have to produce various models with people’s different needs. D. Threat of New Entrants The threat of new entrants is low because there are high barriers to enter the industry. First of all, in order to be able to compete in the automobile industry, a company has to produce massively to achieve large economies of scales to make products accessible and competitive, and since it requires enormous amount of specialized and sophisticated capitals and manufacturing facilities and experienced workforce to mass-produce, there is a huge amount of upfront cost (Academic Minds 2012). In addition, not only the manufacturing startup cost is high, the cost of research and development View as multi-pages

Essay --

INTRODUCTION Advertising can mean many different things in today’s world. When advertising first was developed it was done by would of mouth and the classic flyer or poster, which is the traditional media. Then it moved up to using broadcast media such as radio to help capture a bigger audience. After that it moved towards the television where an even bigger audience could be reached. Lastly companies started to realize the shear amount of traffic that was generated by the Internet. The Internet first started to get popular in the mid 1990’s. Where only people with high tech computers and that could afford the service had the Internet. Of course the Internet did not look the way it does now during that time. There were no pop up ads, java, banners, or graphics that made a consumer purchase a product because they saw it on the Internet. One main reason that there was none of this was because the Internet could only use dial – up. Of course everyone knows how slowly that was, so picture trying to upload or update a website at that pace with huge files. We all know that this would take a very long time eventually making the company lose money. With the turn of the century close by not only did we enter a new century but we entered a new age of the Internet. The introduction of a cable modem drastically increased the Internet population. With speeds up to almost one hundred times faster then dial – up there was no comparison. With this new inven tion companies soon started to ease off on some parts of their advertising campaign and focused more on advertising on the Internet. So what is Internet Advertising? Internet Advertising is a way of marketing services or products on the World Wide Web. This can be done through search engine o... ... right people by increasing the awareness about the product, its benefits and drawbacks. This is important for the success of a business. There is both good and dark side of Internet advertising, including for social networking sites. As alluded to earlier, Internet marketing can manifest in negative, sometimes downright irritating, ways. Advertising malpractice can broach both the ethical and the legal. In e-mail marketing, knowing what constitutes spamming and what is legitimate advertising is extremely important. Internet threw open the plethora of opportunities for enormous scaling of business, thanks to the massive scope of expanding as well as popularizing the business by way of online advertisement. Now, every kind of business no matter big or small businesses can expand itself by way of online advertising where there are massive users across the whole world.

Communication and professional relationships

Explain how you use effective communication in developing positive relationships with children, young people and adults. Why is this important? 1. 1 In developing positive relationships we use effective communication in several ways. We use it to: help us better understand a situation or person which can help to determine our approach when engaging with them. build trust and respect. If individuals feel comfortable speaking with us and feel they can approach us at any time on any subject, they are more likely to co-operate and look favourably on any suggestions made. show that we care about the welfare and future of an individual and will do our best to aid in their success ensure that all parties are agreed upon the same goal, making sure that everyone is clear about the final aim and how it will be achieved. build and maintain a positive working environment where creativity and learning can flourish. It is important to do this because poor communication can lead to misunderstanding s, lack of trust and conflict. Without a positive relationship you are unlikely to gain support and co-operation and find it challenging to achieve a good outcome from any situation.Explain the principles of relationship building with children, young people and adults 1. 2 When trying to develop positive relationships there are several principles to follow. Firstly effective communication is essential. You must be clear in what you say and ensure you have been understood correctly. At the end of a communication you can reiterate your key points and if necessary outline responsibilities and actions. Also be sure to use language appropriate to the person with whom you are communicating.When speaking with young children keep key points to a minimum and ask them to repeat what you have said. Secondly, take time to listen to others and try to understand their point of view. Use active listening techniques to show that you are interested in what they are saying and respond appropriately. Also make sure that, if you tell someone you will get back to them, you do get back to them. This will help engender a sense of trust and respect. It is also essential that you show respect for the person with whom you are communicating.Remember their name and details of how they like to be addressed and issues which are personal to them. Recalling details of their lives adds to the feeling that you are genuinely interested in hem and their welfare. When communicating be sure to acknowledge the individual. Accommodate any religious and cultural beliefs and show that you value these differences. Be considerate of the person's situation trying to understand and accommodate any issues which may influence their feelings, actions and responses.Finally, remain positive and retain a sense of humour. Laughter is a good way to break the ice and relieve tension in a stressful situation. relationships and the way people communicate 1. 3 There are several ways in which social, professional and cultural contexts may affect our relationships and the way we communicate. We must remember that communication is not Just verbal and context will influence the way we act, what we wear, how we communicate and what we say. In a social setting our actions, language and dress may be less formal.If we have colleagues and parents from school as friends outside of school, then we might perhaps greet them with a hug and a wave. Our language might incorporate slang and Jokes and conversation might be more generic and less serious. We might be more casual in our attire and the situation would suggest whether this is acceptable. For example, you would not be expected to attend a party wearing your best suit. The manner in which we communicate socially is also likely to be different from a professional setting.As well as telephone and face to face conversations we might also engage via text message, email and social media sites and we would be unlikely to write a letter to someone we might se e daily. Communications might, for example, utilise text speak and Jargon and not necessarily demand an immediate response if any at all. In a professional context you would be expected to act, speak and dress more formally. Your actions language and clothing should match the severity of the issue which you will address nd show appropriate respect for the location and people with whom you are meeting.If participating in a parent/ teacher meeting at school for example the same people you greeted with a hug the night before would be better greeted with perhaps a handshake to highlight the position you hold in this scenario. Our language would be more formal and depending who was present we might try to eliminate Jargon to ensure clarity and minimise misunderstandings. Similarly again our clothing would be more formal to identify the position we hold and show respect for those involved in any meeting.When contacting people professionally the use of ocial media sites would not be approp riate to discuss any matters relating to school, pupils or staff. Text messages might be appropriate to inform parents/carers of a school social event for example but to arrange a meeting or discuss an important matter it would be more appropriate to speak with a parent/carer or write a letter if the contact needs to be documented. When working with outside agencies email, for ease of use and speed, has become the standard form of communication but again when broaching a sensitive or important issue, a phone call or face to face meeting might be preferred.Emails can easily be misread which can lead to misunderstanding and conflict. When speaking we can use tone of voice to help ensure a point is understood correctly and face to face we can use body language in the same way. The timeframe in which we contact someone or reply to a communication can also affect relationships. When someone has taken the time to contact you they will expect a response to show that you value their contact and it should be made in the same manner or more personally. Responding to a phone call with an email, for example, could be seen as rude and deter future contact.Similarly, elaying a response could suggest that you do not value the input of the individual or consider them or their issue to be important and bring about the same result. Different cultures may also have different standards in terms of behaviour, dress, communication and contact. Actions could be misinterpreted and cause offence leading to the breakdown of a relationship. If you are meeting with someone from a different culture it may be worth doing some research and asking their preferred form of contact etc. to show that you value their beliefs.However, whilst it may be detrimental not to account for cultural differences you could see the same onsequences if you assume differences because of background or race when actually there are none. What skills do you need to communicate with children and young people 2. 1 Co mmunication is still a relatively new thing for children and young people and they may not be used to asking questions and holding conversations. One skill required to communicate effectively is giving children and young people opportunities to speak.As adults we are inclined to think that we know what children are thinking and feeling and try to tell them this or fill the gaps in their speech. Whilst we should ontinue to try and communicate with children as often as possible we should ensure it is a two-way conversation and not a one-way stream of instructions. We should remain patient and allow children time to organise their thoughts and formulate their sentences. When a child is relaxed and at ease they will be more forthcoming.Children may be shy and reluctant to say more than a few words if they feel you are not interested in what they have to say. Using positive body language we can encourage children to speak out. We should come down to the child's level, face them and maint ain eye contact. Remaining focussed on the child rather than ontinuing with another task will confirm your interest and appropriate facial expressions will show that you are listening and have understood what they are saying. Active listening is another key skill.Be interested and make appropriate responses whilst the child is speaking to confirm that you are really listening. Add to this by repeating back what the child has said to ensure your understanding is correct and by giving positive comments when they have finished. Asking open questions will extend the conversation giving the child more practice, boost the child's confidence so they are encouraged to communicate more and model a real onversation for them to learn from. Finally, we must also ensure that communication is appropriate for the child or young person and be able to adapt the style we use.Depending on the age and ability of the child we may be able to simply converse or might need to incorporate visual support or play into the communication. We should not assume children and young people will not understand but instead make our communication clear, use vocabulary which is appropriate to their age and encourage questioning. Give a detailed explanation of how you adapt communication with children and young people for: 2. a The age of the When communicating with younger children you should try choose a setting which is familiar to the child and where they are more confident – their favourite area of the classroom for example.Get down to the level of the child perhaps sitting on the carpet and use body language to make them feel more comfortable – ensure you are facing the child, smile, nod, turn toward them, keep your arms open and remove any barriers between you. Younger children will require more reassurance and perhaps more physical contact. They may feel more confident holding your hand or sitting close together. Vocabulary should be kept simple and sentences short, broken dow n into easy steps. The same point may need to be repeated several times in different ways and it is helpful to provide examples based around their own experiences.If a child is very reluctant to communicate you may want to use puppets to speak through, include pictures or props to help them engage or perhaps incorporate your communication into a favourite game. The attention span of younger children is very short and you must also account for this. Monitor the length of time you spend together and include attention switches to maintain their interest: change your ethod of communication, switch speakers, move location, ask questions etc. Older children and young people will still need to feel comfortable in your company but are more independent and will require less reassurance and physical contact.They are more familiar with the school environment so will find it easier communicate in different settings but will more comfortable in a setting they have used before. Older children oft en view themselves as grown up and will appreciate being treated accordingly. Positive body language will still be beneficial in encouraging a child to peak but it will no longer be necessary to sit on the floor. Language and vocabulary should be more mature and sentences can be more complex. It may also not be necessary to repeat a point so often unless it is something new and above that person's ability level.Examples can be drawn from a variety of sources as their experiences are wider and additional materials should be more sophisticated such as written texts or â€Å"you tube† clips. Older children are more aware of themselves and can be easily embarrassed. They will benefit from confidence boosting reminders of how well they are progressing and positive re-enforcement. They will, however, withdraw and react negatively if patronised, preferring to be treated with respect and spoken to honestly. With age attention span also increases so it is still necessary to include at tention switches to maintain focus but not as frequently. the context of the communication We will encounter children in a variety of situations at school and it will be necessary to adapt our communication accordingly. Primarily our contact will be made inside school during a learning activity. In this case we need to remain quite formal, be directive and model the behaviour we require through our own actions. Ground rules should be laid down in clear, concise Instructions and the learning objectives highlighted to ensure all children fully understand what we expect and are trying to achieve from the lesson.There will be other children in the same area working on of our group but not distract the others. We can do this through tone of voice, choice of vocabulary and supplementary resources but must be wary not to overexcite the group because of the other learners present. If your activity is away from other learners then it may be possible to incorporate physical activity and allow greater expression. Distractions will be plentiful and we will need to encourage and focus our learners through positive re-enforcement and challenges.If appropriate to the task we should encourage discussion through questioning but keep discussion restricted to the subject at hand. In a more social setting, for example the playground, we can be less formal and more relaxed in our approach. This would be reflected in our body language, tone of voice and vocabulary. These times can be used as opportunities to build relationships and get to know the children better. Children can be encouraged to discuss outside nterests and we might share our own experiences to help form a bond.Whilst it may be necessary to give little reminders of school rules to avoid bad behaviour it should not be necessary to outline them in full and they can be made in a more playful and conspiratorial manner – a helpful friend rather than a fgure of authority. Although conversation might be more light he arted we must still remember to maintain the relationship of teacher and pupil. A school trip, however, is a more social event, but still a learning activity and the degree of formality should remain on a similar level to the classroom.The formality f the pupil teacher relationship should remain so the children understand that you â€Å"are in charge†. Children will need to be reminded often of their objectives but communication might be more light hearted and children allowed to speak more freely, discussing outside interests highlighted by the current situation. Outside the school environment they will be excited and more forgetful of their code of conduct. It will not always be possible to speak with the whole group when on a trip so we should communicate through our own behaviour, modelling what we expect from the children: remaining focussed, respectful, and responsible.

Gods or God?

1. Mary Lefkowitz responds to the charges by some secular commentators that religion â€Å"‘poisons’ human life and causes endless violence and suffering† by stating that the â€Å"poison isn't religion; it's monotheism. † 2. â€Å"Openness to discussion and inquiry† and â€Å"[r]espect for a diversity of viewpoints† are some attitudes that contributed to the Athenian idea of â€Å"the cooperative system of government †¦ called democracy. †3. The existence of many different gods offers a more reasonable explanation than monotheism of â€Å"the presence of evil and confusion in the world. † A mortal â€Å"may have had the support of one god but incur the enmity of another, who could attack when the patron god was away†; however in the monotheistic traditions, â€Å"God is omnipresent and always good† and â€Å"mortals must take the blame for whatever goes wrong,† even though God permits evil to exist in t he world he created. 4.The separation between humankind and the gods made it possible for humans â€Å"to speculate about the character and intentions of the gods. † Greek theology allowed people to ask hard questions and encouraged others to learn and to seek all the possible causes of events. Such questions brought philosophy and science to the world. 5. Lefkowitz writes, â€Å"Ancient Greek religion gives an account of the world that in many respects is more plausible than that offered by the monotheistic traditions.† In this context, â€Å"plausible† seems to mean â€Å"reasonable. † The Greek account may be more â€Å"plausible† because â€Å"Greek theology openly discourages blind confidence based on unrealistic hopes that everything will work out in the end. † 6. Lefkowitz certainly makes an excellent point and I definitely agree with her. Religion today seems to be focused too much on blind belief. Thinking seems to create a healthie r environment and some â€Å"healthy skepticism† would definitely be helpful currently in such a stubborn world.

Harpercollins and Social Care Essay

Harpercollins and Social Care Essay Harpercollins and Social Care Essay P1- Potential hazards and the harm that may arise from each in a health and social care setting. The objective of this assignment is to examine health, safety and hazards within a health and social care environment, I will be giving examples of hazards I have witnessed within a health and social care setting (Nursery) and I will explain the potential effects that may occur. Hazard: A hazard can be an accident, it can cause injury and there is a chance of an individual being harmed, or being put into danger, for example a fire hazard may occur if the gas has been left on and someone lights a flame. This is a serious hazard. (Collins English Dictionary –1991, 1994, 1998, 2000, 2003) Placement: The placement I worked at for two weekswas located in south Birmingham, it was a day care centre where children aged 0-5 attended. To enter the nursery there is a gate which is always left open and unattended. There is then a straight pathway which leads straight to the nursery. To enter the nursery you must press the bell or enter a code that only the staffs know of. Once you enter there are two heavy duty doors which are hard to push open and close. The nursery is all on one ground there is no higher ground or lower ground. There is a office and a wash room on the way in to the nursery. The room is rather large and is split into 3 sections separated by gates. 1st section is where babies were, the middle section is where the toddlers/infants were and the 3rd section is where the oldest children were. The section in which the babies were was next to the kitchen and a store room. Where the toddlers were was the main entrance, toilets and the heavy duty doors. It was locked off by the gates though. Also where the children were was the backdoors to where the garden and field was. There was about 30 children and 5 members of staff and 3 students who were on work experience including myself. The physical condition of the children at the nursery were, that they were normal, healthy, regular children who were very curious, vulnerable, active, emotional, very delicate and very young meaning that their awareness to danger and hazards is very limited. Due to them being so vulnerable means that they need to be watched at all times ensuring that they are safe as they may pick anything up. The employees at the nursery were experiences qualified workers; there were 5 members of staff 2 where the babies were 2 where the toddlers were and 1 where the children were, and in each section was a student who was on work experience. As there were 5 members of staff who were qualified they should know about health and safety which can lead to fewer hazards. Also as there were 3 students with no experience this can lead to more hazards and risks. Hazard 1: Front gate left open unattended. People can see that the gates are opened and unattended so they might decide to walk in which may lead to them damaging property, theft or even taking property information. The children may see that the doors are open which can lead to them running out and they might now be able to be stopped as there is no one attending the doors, this can lead to them having an accident or something very serious. The worst possible case is that an intruder can come in and maybe abduct a child from the nursery, which will lead to an investigation and maybe closure of the nursery. Hazard 2: Gates in the nursery left open. They can run out of the section they are suppose to stay in and maybe get their fingers caught in the gates or doors, which can lead to them injuring themselves and having to have professional help. They can run into the open area where the kitchen is, if they enter the kitchen they may mess with the gas switches or and chemical substances left in the bottom draws which they may eat, drink this can cause them serious harm. They may run into store room and mess with the food and cutlery, which will lead to them harming themselves, and damage of

The Abolitionists, Who They Were And How They Became Influential

The Abolitionists, Who They Were And How They Became Influential The term abolitionist generally refers to a dedicated opponent to slavery in the early 19th century America. The abolitionist movement developed slowly in the early 1800s. A movement to abolish slavery gained political acceptance in Britain in the late 1700s. The British abolitionists, led by William Wilberforce in the early 19th century, campaigned against Britains role in the slave trade and sought to outlaw slavery in British colonies. At the same time, Quaker groups in America began working in earnest to abolish slavery in the United States. The first organized group formed to end slavery in America began in Philadelphia in 1775, and the city was a hotbed of abolitionist sentiment in the 1790s, when it was the capital of the United States. Though slavery was successively outlawed in the northern states in the early 1800s, the institution of slavery was firmly entrenched in the South. And agitation against slavery came to be regarded as a major source of discord between regions of the country. In the 1820s anti-slavery factions began spreading from New York and Pennsylvania to Ohio, and the early beginnings of the abolitionist movement began to be felt. At first, the opponents to slavery were considered far outside the mainstream of political thought and abolitionists had little real impact on American life. In the 1830s the movement gathered some momentum. William Lloyd Garrison began publishing The Liberator in Boston, and it became  the most prominent abolitionist newspaper. A pair of wealthy businessmen in New York City, the Tappan brothers, began to finance abolitionist activities. In 1835 the American Anti-Slavery Society began a campaign, funded by the Tappans, to send anti-slavery pamphlets into the South. The pamphlet campaign led to enormous controversy, which included bonfires of seized abolitionist literature being burned in the streets of Charleston, South Carolina. The pamphlet campaign was seen to be impractical. Resistance to the pamphlets galvanized the South against any anti-slavery sentiment, and it made abolitionists in the North realize that it would not be safe to campaign against slavery on southern soil. The northern abolitionists tried other strategies, most prominently the petitioning of Congress. Former president John Quincy Adams, serving in his post-presidency as a Massachusetts congressman, became a prominent anti-slavery voice on Capitol Hill. Under right of petition in the U.S. Constitution, anyone, including slaves, could send petitions to Congress. Adams led a movement to introduce petitions seeking the freedom of slaves, and it so inflamed members of the House of Representatives from the slave states that discussion of slavery was banned in the House chamber. For eight years one of the main battles against slavery took place on Capitol Hill, as Adams battled against what came to be known as the gag rule. In the 1840s a former slave, Frederick Douglass, took to the lecture halls and spoke about his life as a slave. Douglass became a very forceful anti-slavery advocate, and even spent time speaking out against American slavery in Britain and Ireland. By the late 1840s the Whig Party was splitting over the issue of slavery. And disputes which arose when the U.S. acquired enormous territory at the end of the Mexican War brought up the issue of which new states and territories would be slave or free. The Free Soil Party arose to speak out against slavery, and while it didnt became a major political force, it did put the issue of slavery into the mainstream of American politics. Perhaps what brought the abolitionist movement to the forefront more than anything else was a very popular novel, Uncle Toms Cabin. Its author, Harriet Beecher Stowe, a committed abolitionist, was able to craft a tale with sympathetic characters who were either slaves or touched by the evil of slavery. Families would often read the book aloud in their living rooms, and the novel did much to pass abolitionist thought into American homes. Prominent abolitionists included: William Lloyd GarrisonFrederick DouglassAngelina Grimkà © and her sister Sarah Grimkà ©Wendell PhillipsJohn BrownHarriet TubmanHarriet Beecher Stowe The term, of course, comes from the word abolish, and particularly refers to those who wanted to abolish slavery. The Underground Railroad, the loose network of people who assisted escaped slaves to freedom in the northern United States or Canada, could be considered part of the abolitionist movement.

Globalization in Daily Life Assignment Example | Topics and Well Written Essays - 2250 words

Globalization in Daily Life - Assignment Example Many scholars and economist have tried to explain the term globalization as per their own view and opinions. For example, Jos Berghman commented that â€Å"globalization refers to a growing global interconnectedness† (Berghman, 2005, p.6). The term, ‘interconnectedness’ itself explains the core essence of the globalization. The UK Department for International Development (DFID) has given a broad definition of globalization. DFID has identified that the â€Å"increased flows of goods, services, capital, people and information† are the major determinants of globalization which is â€Å"driven by technological advances and reductions in the cost of international transaction† (Zajda, 2005, p.294).  Therefore, primarily, international trade and technological advancements have facilitated the process of globalization and this has developed medium for exchanging ideas, views, tangible & intangible capital, factors of productions etc. This process has crea ted a better scope for the development of economic, social, cultural and international relation. In our every step of daily life, we can feel of the presence of this development encouraged by globalization.  For example, the product developed using Japanese technologies like Japanese cars is dominating in the global automobile sectors. On the other hand, Italian cuisine like ‘Pizza’ is one of the popular food items of the people living in American and Asian countries. Moreover, Chinese cost-effective production process has led to encouraging many manufacturers like Nike to expand their business in China, and many multinational corporations are trying to enter in emerging marketing like India, Taiwan, China etc. These examples are a proper reflection as an outcome of globalization. In order to facilitate the process of international trade, the trade agreement between and/or among different countries have played a very significant role as it helps to grow a country with significant amount of foreign direct investments (FDI) which creates industrialization causing growth in aggregate demand and supply, and an economy can achieve equilibrium growth. Recently, U.S. and Korea have entered into free trade agreement known as KORUS FTA, according to which the U.S. MNCs can have greater accesses in the Korean market, and Korean automobile manufacturer can enjoy a significantly reduced tariff in U.S. automobile market (U.S. International Trade Commission, 2011). The U.S. automobile sector is already crowded with a number of domestic and foreign automobile companies. However, as per this agreement, the Korean companies can have better access to the automobile market as they are able to offer cars at much-reduced cost increasing the competition. The competition is one of the healthy sign for economic development.

Man vs women superior Im taking the man side Essay

Man vs women superior Im taking the man side - Essay Example They like challenges and this is the reason why they are physically much stronger than the women. Ladies and gentlemen, I remark from renowned evidence that has come to the fore that men are able to execute things better than their female counterparts because they know what is going on with them rather than their female partners who know little about the environmental issues. Men therefore know it better how to tackle the problems and thus analyze the same in a much rigorous manner before approaching it. Also men are known to decide their course of action much earlier than their female counterparts. This is because men take less time to analyze and thus make up their mind. Since men are known to be tough taskmasters, they get the job done quickly whereas the women take a lot of time to think through and then go about executing a task or an action under their aegis (May, 2011). Men therefore decide it quickly what to do with their actions whereas the women take advice from others and often are tied up within confusing patterns even after they have taken one such decision. What is even more comparatively driven is the fact that women lack the mental strength and are more prone to crying their heart out and expressing their concerns than the men. This is the reason why one would see more women shedding tears and fewer men doing it on a regular basis. Women believe that it is not their duty to go through the physical and mental drills much like what their male counterparts do on a regular basis (Connell, 2011). Hence masculinity and femininity are two sides of the same coin and deserve attention for a number of reasons. However the basic premise is much the same yet the men are stronger than women and known to enjoy the rigors of life well. May I add here in the end that men make the world tougher yet the women make it sweeter. It is the combination of

Evaluation of Deterrence Theory Research Paper Example | Topics and Well Written Essays - 1500 words

Evaluation of Deterrence Theory - Research Paper Example In my evaluation, I use the evaluation method proposed by Akers and Seller. In this technique, the theory is evaluated using its scope, logical consistency, parsimony, testability, empirical validity, and its usefulness and policy implication. A major advantage of this method that it can give us the chance to evaluate almost all the aspects of this theory. Theory Discussion This theory uses the idea that fear of punishment or negative consequences resulting from committing a crime can cause individuals to refrain from committing offenses (Maimon, 2012). One of the things this theory uses in explaining criminology is human rationality. It says that human nature is motivated to do something that has more gains than losses. Therefore, if someone sees that he will have more loss than gain from a crime when he is caught, he will be motivated to refrain from the crime. This theory thus proposes that severe punishments should be imposed on crimes and offenses to increase the risks that a pe rson exposes himself to when committing them. The theory also uses the concept of an individual’s free will and the power of a person to make calculated choices in explaining crime. This theory states that people commit crimes due to the drive to do so from their free will without being directed to do so by someone else. However, it indicates that in making a choice to commit a crime individuals to analyze the gains and losses which might result from the choices they want to make. As a result, the choices they make are always calculated to make sure they maximize gains while minimizing risks. If severe punishments are imposed on crimes they will make the crimes to be less attractive and hence make individuals refrain from them. This theory explains individual offending and how people can be deterred from committing crimes. It suggests that imposing formal legal punishments can deter individuals from offending. However, according to Maimone al (2012), the theory explains that the deterrent effect of these formal legal punishments depends on their severity, certainty, and celebrity.

Made in Chelsea analysis of an episode Essay Example for Free

Made in Chelsea analysis of an episode Essay From the episode of Made In Chelsea I watched, I can say that the representations we have of upwardly mobile young city dwellers are that they are social-oriented, whose lives seem to be some care-free that they can cavort around various places in London—and the world—without any problems. We also only see characters of a certain age range—none are, we assume, above the age of thirty—of which the majority have no jobs or business, leading us to believe that they come from families of ‘old money’, and so having a job themselves would seem rather pointless. Saying that, there are a few characters who do possess their own business or thereabouts. However, our perceptions of the characters are very one sided, as we are constricted to seeing only one side of that character—the one that fits their current storyline the best. This prevents us from seeing, per se, the kind heartedness of a character that has just cheated on their partner. The words ‘characters’ and ‘storylines’ fit well with my next point; the conversations and the events that take place throughout the episode seem far too rehearsed and coincidental for them to be actual ‘reality’. Location shots are used of London sights and attractions to establish the setting of the scene. They also are only of Central London attractions, and the shops and restaurants et al all seem to highlight the wealth of the individuals who shop there, eat there etc. Reactions, for the majority of the show, are shown using over-the-shoulder shots to portray the reaction of the person who is being told something. There is also usage of eye line matching shots that show you what the character may have been looking at from their angle. The episode seems to comprise of short segments that have then been edited in post production so that they can seek out the most entertaining of segments. This is obvious as the episode transitions from one group of people at a restaurant to a boxing arena and then back to the restaurant again. Tzvetan Torodov’s narrative theory that conventional narratives are structured into five stages; Equilibrium—disruption—recognition—repair—reinstatement, could be present within the episode, as you can apply it to the situation between Louis, Spencer and Jamie (the love triangle storyline). The fact that it fits so well with Torodov’s theory does support the question â€Å"How much of Made In Chelsea is actually reality? †

The Youth Offenders Program :: essays research papers

The Youth Offenders Program   Ã‚  Ã‚  Ã‚  Ã‚  To be honest, I was really pissed off that I had to enter the Zona Seca program to begin with. My so-called infraction was a simple case of being in the wrong place at the wrong time. I am a full time student who works at least twenty-eight hours a week and is extremely pressed for time. The commute from Los Angeles was an extreme inconvenience. Just had to get that off my chest. Do not be fooled, I am extremely grateful for the opportunity to attend this program. I just wish I could have took it here in L.A Surprisingly enough, the Zona Seca program was nothing like I expected. Going into the program I expected lengthy and boring lectures by condescending bureaucrats. To my surprise, the classes were interesting and informative. Our instructors both at the Rehabilitation Institute and the Zona Seca office were very understanding. More programs that are prevention orientated rather than reactionary like Zona Seca are needed. Before the first class session I viewed Zona Seca as a kind of punishment; afterwards more like a therapy/counseling session. The visit with the coroner really struck a nerve. When the coroner started talking about the way young adults drink alcohol as opposed to the way most adults do I could not help but think of all the times I have gotten belligerent. He made the statement that most young people drink to get to drunk. I could not agree more. Although I do drink because I like the taste of alcohol, that taste was definitely acquired. When I first started drinking it was for the sole purpose of getting drunk. Death as a result of to much alcohol was something I was completely oblivious to. Imagining how close to permanent unconsciousness I may have been is extremely scary. I can remember being so drunk in Rosa Rito Mexico that I woke up the next morning not remembering a damn thing from the night before. That includes puking up my dinner, the seven hundred and fifty-ml bottle of Bacardi Limon and the ten or fifteen other mixed drinks I had. If my friends did not tell me of the details from the previous night I would had never known what happened. The coroner’s report really made me look at the way I drink. I’m not going to stop drinking, but I am going to be a lot more responsible and careful when I do.

Statistics for Business and Economics

Openmirrors. com CUMULATIVE PROBABILITIES FOR THE STANDARD NORMAL DISTRIBUTION Cumulative probability Entries in this table give the area under the curve to the left of the z value. For example, for z = –. 85, the cumulative probability is . 1977. z 0 z 3. 0 2. 9 2. 8 2. 7 2. 6 2. 5 2. 4 2. 3 2. 2 2. 1 2. 0 1. 9 1. 8 1. 7 1. 6 1. 5 1. 4 1. 3 1. 2 1. 1 1. 0 . 9 . 8 . 7 . 6 . 5 . 4 . 3 . 2 . 1 . 0 .00 . 0013 . 0019 . 0026 . 0035 . 0047 . 0062 . 0082 . 0107 . 0139 . 0179 . 0228 . 0287 . 0359 . 0446 . 0548 . 0668 . 0808 . 0968 . 1151 . 1357 . 1587 . 1841 . 2119 . 2420 . 2743 . 3085 . 3446 . 3821 . 4207 . 4602 . 5000 01 . 0013 . 0018 . 0025 . 0034 . 0045 . 0060 . 0080 . 0104 . 0136 . 0174 . 0222 . 0281 . 0351 . 0436 . 0537 . 0655 . 0793 . 0951 . 1131 . 1335 . 1562 . 1814 . 2090 . 2389 . 2709 . 3050 . 3409 . 3783 . 4168 . 4562 . 4960 .02 . 0013 . 0018 . 0024 . 0033 . 0044 . 0059 . 0078 . 0102 . 0132 . 0170 . 0217 . 0274 . 0344 . 0427 . 0526 . 0643 . 0778 . 0934 . 1112 . 1314 . 1539 . 1788 . 2061 . 2358 . 2676 . 3015 . 3372 . 3745 . 4129 . 4522 . 4920 .03 . 0012 . 0017 . 0023 . 0032 . 0043 . 0057 . 0075 . 0099 . 0129 . 0166 . 0212 . 0268 . 0336 . 0418 . 0516 . 0630 . 0764 . 0918 . 1093 . 1292 . 1515 . 1762 . 2033 . 2327 . 643 . 2981 . 3336 . 3707 . 4090 . 4483 . 4880 .04 . 0012 . 0016 . 0023 . 0031 . 0041 . 0055 . 0073 . 0096 . 0125 . 0162 . 0207 . 0262 . 0329 . 0409 . 0505 . 0618 . 0749 . 0901 . 1075 . 1271 . 1492 . 1736 . 2005 . 2296 . 2611 . 2946 . 3300 . 3669 . 4052 . 4443 . 4840 .05 . 0011 . 0016 . 0022 . 0030 . 0040 . 0054 . 0071 . 0094 . 0122 . 0158 . 0202 . 0256 . 0322 . 0401 . 0495 . 0606 . 0735 . 0885 . 1056 . 1251 . 1469 . 1711 . 1977 . 2266 . 2578 . 2912 . 3264 . 3632 . 4013 . 4404 . 4801 .06 . 0011 . 0015 . 0021 . 0029 . 0039 . 0052 . 0069 . 0091 . 0119 . 0154 . 0197 . 0250 . 0314 . 0392 . 0485 . 0594 . 0721 . 0869 . 038 . 1230 . 1446 . 1685 . 1949 . 2236 . 2546 . 2877 . 3228 . 3594 . 3974 . 4364 . 4761 .07 . 0011 . 0015 . 0021 . 0028 . 0038 . 0051 . 0068 . 0089 . 0116 . 0150 . 0192 . 0244 . 0307 . 0384 . 0475 . 0582 . 0708 . 0853 . 1020 . 1210 . 1423 . 1660 . 1922 . 2206 . 2514 . 2843 . 3192 . 3557 . 3936 . 4325 . 4721 .08 . 0010 . 0014 . 0020 . 0027 . 0037 . 0049 . 0066 . 0087 . 0113 . 0146 . 0188 . 0239 . 0301 . 0375 . 0465 . 0571 . 0694 . 0838 . 1003 . 1190 . 1401 . 1635 . 1894 . 2177 . 2483 . 2810 . 3156 . 3520 . 3897 . 4286 . 4681 .09 . 0010 . 0014 . 0019 . 0026 . 0036 . 0048 . 0064 . 0084 . 0110 . 0143 . 0183 . 0233 . 294 . 0367 . 0455 . 0559 . 0681 . 0823 . 0985 . 1170 . 1379 . 1611 . 1867 . 2148 . 2451 . 2776 . 3121 . 3483 . 3859 . 4247 . 4641 CUMULATIVE PROBABILITIES FOR THE STANDARD NORMAL DISTRIBUTION Cumulative probability Entries in the table give the area under the curve to the left of the z value. For example, for z = 1. 25, the cumulative probability is . 8944. 0 z z . 0 . 1 . 2 . 3 . 4 . 5 . 6 . 7 . 8 . 9 1. 0 1. 1 1. 2 1. 3 1. 4 1. 5 1. 6 1. 7 1. 8 1. 9 2. 0 2. 1 2. 2 2. 3 2. 4 2. 5 2. 6 2. 7 2. 8 2. 9 3. 0 .00 . 5000 . 5398 . 5793 . 6179 . 6554 . 6915 . 7257 . 7580 . 7881 . 8159 . 8413 . 8643 . 8849 . 9032 . 192 . 9332 . 9452 . 9554 . 9641 . 9713 . 9772 . 9821 . 9861 . 9893 . 9918 . 9938 . 9953 . 9965 . 9974 . 9981 . 9987 .01 . 5040 . 5438 . 5832 . 6217 . 6591 . 6950 . 7291 . 7611 . 7910 . 8186 . 8438 . 8665 . 8869 . 9049 . 9207 . 9345 . 9463 . 9564 . 9649 . 9719 . 9778 . 9826 . 9864 . 9896 . 9920 . 9940 . 9955 . 9966 . 9975 . 9982 . 9987 .02 . 5080 . 5478 . 5871 . 6255 . 6628 . 6985 . 7324 . 7642 . 7939 . 8212 . 8461 . 8686 . 8888 . 9066 . 9222 . 9357 . 9474 . 9573 . 9656 . 9726 . 9783 . 9830 . 9868 . 9898 . 9922 . 9941 . 9956 . 9967 . 9976 . 9982 . 9987 .03 . 5120 . 5517 . 5910 . 6293 . 6664 . 7019 . 7357 . 7673 . 967 . 8238 . 8485 . 8708 . 8907 . 9082 . 9236 . 9370 . 9484 . 9582 . 9664 . 9732 . 9788 . 9834 . 9871 . 9901 . 9925 . 9943 . 9957 . 9968 . 9977 . 9983 . 9988 .04 . 5160 . 5557 . 5948 . 6331 . 6700 . 7054 . 7389 . 7704 . 7995 . 8264 . 8508 . 8729 . 8925 . 9099 . 9251 . 938 2 . 9495 . 9591 . 9671 . 9738 . 9793 . 9838 . 9875 . 9904 . 9927 . 9945 . 9959 . 9969 . 9977 . 9984 . 9988 .05 . 5199 . 5596 . 5987 . 6368 . 6736 . 7088 . 7422 . 7734 . 8023 . 8289 . 8531 . 8749 . 8944 . 9115 . 9265 . 9394 . 9505 . 9599 . 9678 . 9744 . 9798 . 9842 . 9878 . 9906 . 9929 . 9946 . 9960 . 9970 . 9978 . 9984 . 9989 .06 . 5239 . 636 . 6026 . 6406 . 6772 . 7123 . 7454 . 7764 . 8051 . 8315 . 8554 . 8770 . 8962 . 9131 . 9279 . 9406 . 9515 . 9608 . 9686 . 9750 . 9803 . 9846 . 9881 . 9909 . 9931 . 9948 . 9961 . 9971 . 9979 . 9985 . 9989 .07 . 5279 . 5675 . 6064 . 6443 . 6808 . 7157 . 7486 . 7794 . 8078 . 8340 . 8577 . 8790 . 8980 . 9147 . 9292 . 9418 . 9525 . 9616 . 9693 . 9756 . 9808 . 9850 . 9884 . 9911 . 9932 . 9949 . 9962 . 9972 . 9979 . 9985 . 9989 .08 . 5319 . 5714 . 6103 . 6480 . 6844 . 7190 . 7517 . 7823 . 8106 . 8365 . 8599 . 8810 . 8997 . 9162 . 9306 . 9429 . 9535 . 9625 . 9699 . 9761 . 9812 . 9854 . 9887 . 9913 . 9934 . 9951 . 963 . 9973 . 9980 . 9986 . 9990 .09 . 53 59 . 5753 . 6141 . 6517 . 6879 . 7224 . 7549 . 7852 . 8133 . 8389 . 8621 . 8830 . 9015 . 9177 . 9319 . 9441 . 9545 . 9633 . 9706 . 9767 . 9817 . 9857 . 9890 . 9916 . 9936 . 9952 . 9964 . 9974 . 9981 . 9986 . 9990 STATISTICS FOR BUSINESS AND ECONOMICS 11e This page intentionally left blank STATISTICS FOR BUSINESS AND ECONOMICS 11e David R. Anderson University of Cincinnati Dennis J. Sweeney University of Cincinnati Thomas A. Williams Rochester Institute of Technology Statistics for Business and Economics, Eleventh Edition David R. Anderson, Dennis J. Sweeney, Thomas A.Williams VP/Editorial Director: Jack W. Calhoun Publisher: Joe Sabatino Senior Acquisitions Editor: Charles McCormick, Jr. Developmental Editor: Maggie Kubale Editorial Assistant: Nora Heink Marketing Communications Manager: Libby Shipp Content Project Manager: Jacquelyn K Featherly Media Editor: Chris Valentine Manufacturing Coordinator: Miranda Kipper Production House/Compositor: MPS Limited, A Macmillan Company Senio r Art Director: Stacy Jenkins Shirley Internal Designer: Michael Stratton/cmiller design Cover Designer: Craig Ramsdell Cover Images: Getty Images/GlowImages Photography Manager: John Hill 2011, 2008 South-Western, Cengage Learning ALL RIGHTS RESERVED. No part of this work covered by the copyright herein may be reproduced, transmitted, stored or used in any form or by any means graphic, electronic, or mechanical, including but not limited to photocopying, recording, scanning, digitizing, taping, Web distribution, information networks, or information storage and retrieval systems, except as permitted under Section 107 or 108 of the 1976 United States Copyright Act, without the prior written permission of the publisher.For product information and technology assistance, contact us at Cengage Learning Customer & Sales Support, 1-800-354-9706 For permission to use material from this text or product, submit all requests online at cengage. com/permissions Further permissions questions can be emailed to [email  protected] com ExamView  ® is a registered trademark of eInstruction Corp. Windows is a registered trademark of the Microsoft Corporation used herein under license.Macintosh and Power Macintosh are registered trademarks of Apple Computer, Inc. used herein under license. Library of Congress Control Number: 2009932190 Student Edition ISBN 13: 978-0-324-78325-4 Student Edition ISBN 10: 0-324-78325-6 Instructor's Edition ISBN 13: 978-0-538-45149-9 Instructor's Edition ISBN 10: 0-538-45149-1 South-Western Cengage Learning 5191 Natorp Boulevard Mason, OH 45040 USA Cengage Learning products are represented in Canada by Nelson Education, Ltd.For your course and learning solutions, visit www. cengage. com Purchase any of our products at your local college store or at our preferred online store www. ichapters. com Printed in the United States of America 1 2 3 4 5 6 7 13 12 11 10 09 Dedicated to Marcia, Cherri, and Robbie This page intentionally left blank Brief Conte ntsPreface xxv About the Authors xxix Chapter 1 Data and Statistics 1 Chapter 2 Descriptive Statistics: Tabular and Graphical Presentations 31 Chapter 3 Descriptive Statistics: Numerical Measures 85 Chapter 4 Introduction to Probability 148 Chapter 5 Discrete Probability Distributions 193 Chapter 6 Continuous Probability Distributions 232 Chapter 7 Sampling and Sampling Distributions 265 Chapter 8 Interval Estimation 308 Chapter 9 Hypothesis Tests 348 Chapter 10 Inference About Means and Proportions with Two Populations 406 Chapter 11 Inferences About Population Variances 448 Chapter 12 Tests of Goodness of Fit and Independence 472 Chapter 13 Experimental Design and Analysis of Variance 506 Chapter 14 Simple Linear Regression 560 Chapter 15 Multiple Regression 642 Chapter 16 Regression Analysis: ModelBuilding 712 Chapter 17 Index Numbers 763 Chapter 18 Time Series Analysis and Forecasting 784 Chapter 19 Nonparametric Methods 855 Chapter 20 Statistical Methods for Quality Control 903 Chapter 21 Decision Analysis 937 Chapter 22 Sample Survey On Website Appendix A References and Bibliography 976 Appendix B Tables 978 Appendix C Summation Notation 1005 Appendix D Self-Test Solutions and Answers to Even-Numbered Exercises 1007 Appendix E Using Excel Functions 1062 Appendix F Computing p-Values Using Minitab and Excel 1067 Index 1071 This page intentionally left blank Contents Preface xxv About the Authors xxix Chapter 1 Data and Statistics 1 Statistics in Practice: BusinessWeek 2 1. 1 Applications in Business and Economics 3 Accounting 3 Finance 4 Marketing 4 Production 4 Economics 4 1. Data 5 Elements, Variables, and Observations 5 Scales of Measurement 6 Categorical and Quantitative Data 7 Cross-Sectional and Time Series Data 7 1. 3 Data Sources 10 Existing Sources 10 Statistical Studies 11 Data Acquisition Errors 13 1. 4 Descriptive Statistics 13 1. 5 Statistical Inference 15 1. 6 Computers and Statistical Analysis 17 1. 7 Data Mining 17 1. 8 Ethical Guidelines for Statistical Practice 18 Summary 20 Glossary 20 Supplementary Exercises 21 Appendix: An Introduction to StatTools 28 Chapter 2 Descriptive Statistics: Tabular and Graphical Presentations 31 Statistics in Practice: Colgate-Palmolive Company 32 2. 1 Summarizing Categorical Data 33 Frequency Distribution 33 Relative Frequency and Percent Frequency Distributions 34 Bar Charts and Pie Charts 34 x Contents 2. Summarizing Quantitative Data 39 Frequency Distribution 39 Relative Frequency and Percent Frequency Distributions 41 Dot Plot 41 Histogram 41 Cumulative Distributions 43 Ogive 44 2. 3 Exploratory Data Analysis: The Stem-and-Leaf Display 48 2. 4 Crosstabulations and Scatter Diagrams 53 Crosstabulation 53 Simpson’s Paradox 56 Scatter Diagram and Trendline 57 Summary 63 Glossary 64 Key Formulas 65 Supplementary Exercises 65 Case Problem 1: Pelican Stores 71 Case Problem 2: Motion Picture Industry 72 Appendix 2. 1 Using Minitab for Tabular and Graphical Presentations 73 Appendi x 2. 2 Using Excel for Tabular and Graphical Presentations 75 Appendix 2. 3 Using StatTools for Tabular and Graphical Presentations 84 Chapter 3 Descriptive Statistics: Numerical Measures 85 Statistics in Practice: Small Fry Design 86 3. Measures of Location 87 Mean 87 Median 88 Mode 89 Percentiles 90 Quartiles 91 3. 2 Measures of Variability 95 Range 96 Interquartile Range 96 Variance 97 Standard Deviation 99 Coefficient of Variation 99 3. 3 Measures of Distribution Shape, Relative Location, and Detecting Outliers 102 Distribution Shape 102 z-Scores 103 Chebyshev’s Theorem 104 Empirical Rule 105 Detecting Outliers 106 Contents xi 3. 4 Exploratory Data Analysis 109 Five-Number Summary 109 Box Plot 110 3. 5 Measures of Association Between Two Variables 115 Covariance 115 Interpretation of the Covariance 117 Correlation Coefficient 119 Interpretation of the Correlation Coefficient 120 3. The Weighted Mean and Working with Grouped Data 124 Weighted Mean 124 Grouped Data 125 Summ ary 129 Glossary 130 Key Formulas 131 Supplementary Exercises 133 Case Problem 1: Pelican Stores 137 Case Problem 2: Motion Picture Industry 138 Case Problem 3: Business Schools of Asia-Pacific 139 Case Problem 4: Heavenly Chocolates Website Transactions 139 Appendix 3. 1 Descriptive Statistics Using Minitab 142 Appendix 3. 2 Descriptive Statistics Using Excel 143 Appendix 3. 3 Descriptive Statistics Using StatTools 146 Chapter 4 Introduction to Probability 148 Statistics in Practice: Oceanwide Seafood 149 4. 1 Experiments, Counting Rules, and Assigning Probabilities 150 Counting Rules, Combinations, and Permutations 151 Assigning Probabilities 155 Probabilities for the KP&L Project 157 4. 2 Events and Their Probabilities 160 4. 3 Some Basic Relationships of Probability 164 Complement of an Event 164 Addition Law 165 4. 4 Conditional Probability 171 Independent Events 174 Multiplication Law 174 4. Bayes’ Theorem 178 Tabular Approach 182 Summary 184 Glossary 184 xii Contents K ey Formulas 185 Supplementary Exercises 186 Case Problem: Hamilton County Judges 190 Chapter 5 Discrete Probability Distributions 193 Statistics in Practice: Citibank 194 5. 1 Random Variables 194 Discrete Random Variables 195 Continuous Random Variables 196 5. 2 Discrete Probability Distributions 197 5. 3 Expected Value and Variance 202 Expected Value 202 Variance 203 5. 4 Binomial Probability Distribution 207 A Binomial Experiment 208 Martin Clothing Store Problem 209 Using Tables of Binomial Probabilities 213 Expected Value and Variance for the Binomial Distribution 214 5. Poisson Probability Distribution 218 An Example Involving Time Intervals 218 An Example Involving Length or Distance Intervals 220 5. 6 Hypergeometric Probability Distribution 221 Summary 225 Glossary 225 Key Formulas 226 Supplementary Exercises 227 Appendix 5. 1 Discrete Probability Distributions with Minitab 230 Appendix 5. 2 Discrete Probability Distributions with Excel 230 Chapter 6 Continuous Probability D istributions 232 Statistics in Practice: Procter & Gamble 233 6. 1 Uniform Probability Distribution 234 Area as a Measure of Probability 235 6. 2 Normal Probability Distribution 238 Normal Curve 238 Standard Normal Probability Distribution 40 Computing Probabilities for Any Normal Probability Distribution 245 Grear Tire Company Problem 246 6. 3 Normal Approximation of Binomial Probabilities 250 6. 4 Exponential Probability Distribution 253 Computing Probabilities for the Exponential Distribution 254 Relationship Between the Poisson and Exponential Distributions 255 Contents xiii Summary 257 Glossary 258 Key Formulas 258 Supplementary Exercises 258 Case Problem: Specialty Toys 261 Appendix 6. 1 Continuous Probability Distributions with Minitab 262 Appendix 6. 2 Continuous Probability Distributions with Excel 263 Chapter 7 Sampling and Sampling Distributions 265 Statistics in Practice: MeadWestvaco Corporation 266 7. 1 The Electronics Associates Sampling Problem 267 7. Selecting a Sam ple 268 Sampling from a Finite Population 268 Sampling from an Infinite Population 270 7. 3 Point Estimation 273 Practical Advice 275 7. 4 Introduction to Sampling Distributions 276 _ 7. 5 Sampling Distribution of x 278 _ Expected Value of x 279 _ Standard Deviation of x 280 _ Form of the Sampling Distribution of x 281 _ Sampling Distribution of x for the EAI Problem 283 _ Practical Value of the Sampling Distribution of x 283 Relationship Between the Sample Size and the Sampling _ Distribution of x 285 _ 7. 6 Sampling Distribution of p 289 _ Expected Value of p 289 _ Standard Deviation of p 290 _ Form of the Sampling Distribution of p 291 _ Practical Value of the Sampling Distribution of p 291 7. Properties of Point Estimators 295 Unbiased 295 Efficiency 296 Consistency 297 7. 8 Other Sampling Methods 297 Stratified Random Sampling 297 Cluster Sampling 298 Systematic Sampling 298 Convenience Sampling 299 Judgment Sampling 299 Summary 300 Glossary 300 Key Formulas 301 xiv Contents Su pplementary Exercises 302 _ Appendix 7. 1 The Expected Value and Standard Deviation of x 304 Appendix 7. 2 Random Sampling with Minitab 306 Appendix 7. 3 Random Sampling with Excel 306 Appendix 7. 4 Random Sampling with StatTools 307 Chapter 8 Interval Estimation 308 Statistics in Practice: Food Lion 309 8. 1 Population Mean: Known 310 Margin of Error and the Interval Estimate 310 Practical Advice 314 8. Population Mean: Unknown 316 Margin of Error and the Interval Estimate 317 Practical Advice 320 Using a Small Sample 320 Summary of Interval Estimation Procedures 322 8. 3 Determining the Sample Size 325 8. 4 Population Proportion 328 Determining the Sample Size 330 Summary 333 Glossary 334 Key Formulas 335 Supplementary Exercises 335 Case Problem 1: Young Professional Magazine 338 Case Problem 2: Gulf Real Estate Properties 339 Case Problem 3: Metropolitan Research, Inc. 341 Appendix 8. 1 Interval Estimation with Minitab 341 Appendix 8. 2 Interval Estimation with Excel 343 Appendix 8. 3 Interval Estimation with StatTools 346 Chapter 9 Hypothesis Tests 348 Statistics in Practice: John Morrell & Company 349 9. Developing Null and Alternative Hypotheses 350 The Alternative Hypothesis as a Research Hypothesis 350 The Null Hypothesis as an Assumption to Be Challenged 351 Summary of Forms for Null and Alternative Hypotheses 352 9. 2 Type I and Type II Errors 353 9. 3 Population Mean: Known 356 One-Tailed Test 356 Two-Tailed Test 362 Summary and Practical Advice 365 Contents xv Relationship Between Interval Estimation and Hypothesis Testing 366 9. 4 Population Mean: Unknown 370 One-Tailed Test 371 Two-Tailed Test 372 Summary and Practical Advice 373 9. 5 Population Proportion 376 Summary 379 9. 6 Hypothesis Testing and Decision Making 381 9. 7 Calculating the Probability of Type II Errors 382 9. Determining the Sample Size for a Hypothesis Test About a Population Mean 387 Summary 391 Glossary 392 Key Formulas 392 Supplementary Exercises 393 Case Problem 1: Quality A ssociates, Inc. 396 Case Problem 2: Ethical Behavior of Business Students at Bayview University 397 Appendix 9. 1 Hypothesis Testing with Minitab 398 Appendix 9. 2 Hypothesis Testing with Excel 400 Appendix 9. 3 Hypothesis Testing with StatTools 404 Chapter 10 Inference About Means and Proportions with Two Populations 406 Statistics in Practice: U. S. Food and Drug Administration 407 10. 1 Inferences About the Difference Between Two Population Means: 1 and 2 Known 408 Interval Estimation of 1 – 2 408 Hypothesis Tests About 1 – 2 410 Practical Advice 412 10. Inferences About the Difference Between Two Population Means: 1 and 2 Unknown 415 Interval Estimation of 1 – 2 415 Hypothesis Tests About 1 – 2 417 Practical Advice 419 10. 3 Inferences About the Difference Between Two Population Means: Matched Samples 423 10. 4 Inferences About the Difference Between Two Population Proportions 429 Interval Estimation of p1 – p2 429 Hypothesis Tests About p1 â⠂¬â€œ p2 431 Summary 436 xvi Contents Glossary 436 Key Formulas 437 Supplementary Exercises 438 Case Problem: Par, Inc. 441 Appendix 10. 1 Inferences About Two Populations Using Minitab 442 Appendix 10. 2 Inferences About Two Populations Using Excel 444 Appendix 10. Inferences About Two Populations Using StatTools 446 Chapter 11 Inferences About Population Variances 448 Statistics in Practice: U. S. Government Accountability Office 449 11. 1 Inferences About a Population Variance 450 Interval Estimation 450 Hypothesis Testing 454 11. 2 Inferences About Two Population Variances 460 Summary 466 Key Formulas 467 Supplementary Exercises 467 Case Problem: Air Force Training Program 469 Appendix 11. 1 Population Variances with Minitab 470 Appendix 11. 2 Population Variances with Excel 470 Appendix 11. 3 Population Standard Deviation with StatTools 471 Chapter 12 Tests of Goodness of Fit and Independence 472 Statistics in Practice: United Way 473 12. Goodness of Fit Test: A Multinomial Pop ulation 474 12. 2 Test of Independence 479 12. 3 Goodness of Fit Test: Poisson and Normal Distributions 487 Poisson Distribution 487 Normal Distribution 491 Summary 496 Glossary 497 Key Formulas 497 Supplementary Exercises 497 Case Problem: A Bipartisan Agenda for Change 501 Appendix 12. 1 Tests of Goodness of Fit and Independence Using Minitab 502 Appendix 12. 2 Tests of Goodness of Fit and Independence Using Excel 503 Chapter 13 Experimental Design and Analysis of Variance 506 Statistics in Practice: Burke Marketing Services, Inc. 507 13. 1 An Introduction to Experimental Design and Analysis of Variance 508 Contents xviiData Collection 509 Assumptions for Analysis of Variance 510 Analysis of Variance: A Conceptual Overview 510 13. 2 Analysis of Variance and the Completely Randomized Design 513 Between-Treatments Estimate of Population Variance 514 Within-Treatments Estimate of Population Variance 515 Comparing the Variance Estimates: The F Test 516 ANOVA Table 518 Computer Results for Analysis of Variance 519 Testing for the Equality of k Population Means:An Observational Study 520 13. 3 Multiple Comparison Procedures 524 Fisher’s LSD 524 Type I Error Rates 527 13. 4 Randomized Block Design 530 Air Traffic Controller Stress Test 531 ANOVA Procedure 532 Computations and Conclusions 533 13. Factorial Experiment 537 ANOVA Procedure 539 Computations and Conclusions 539 Summary 544 Glossary 545 Key Formulas 545 Supplementary Exercises 547 Case Problem 1: Wentworth Medical Center 552 Case Problem 2: Compensation for Sales Professionals 553 Appendix 13. 1 Analysis of Variance with Minitab 554 Appendix 13. 2 Analysis of Variance with Excel 555 Appendix 13. 3 Analysis of Variance with StatTools 557 Chapter 14 Simple Linear Regression 560 Statistics in Practice: Alliance Data Systems 561 14. 1 Simple Linear Regression Model 562 Regression Model and Regression Equation 562 Estimated Regression Equation 563 14. 2 Least Squares Method 565 14. Coefficient of Determ ination 576 Correlation Coefficient 579 14. 4 Model Assumptions 583 14. 5 Testing for Significance 585 Estimate of 2 585 t Test 586 xviii Contents Confidence Interval for 1 587 F Test 588 Some Cautions About the Interpretation of Significance Tests 590 14. 6 Using the Estimated Regression Equation for Estimation and Prediction 594 Point Estimation 594 Interval Estimation 594 Confidence Interval for the Mean Value of y 595 Prediction Interval for an Individual Value of y 596 14. 7 Computer Solution 600 14. 8 Residual Analysis: Validating Model Assumptions 605 Residual Plot Against x 606 Residual Plot Against y 607 ? Standardized Residuals 607 Normal Probability Plot 610 14. Residual Analysis: Outliers and Influential Observations 614 Detecting Outliers 614 Detecting Influential Observations 616 Summary 621 Glossary 622 Key Formulas 623 Supplementary Exercises 625 Case Problem 1: Measuring Stock Market Risk 631 Case Problem 2: U. S. Department of Transportation 632 Case Problem 3: Alu mni Giving 633 Case Problem 4: PGA Tour Statistics 633 Appendix 14. 1 Calculus-Based Derivation of Least Squares Formulas 635 Appendix 14. 2 A Test for Significance Using Correlation 636 Appendix 14. 3 Regression Analysis with Minitab 637 Appendix 14. 4 Regression Analysis with Excel 638 Appendix 14. 5 Regression Analysis with StatTools 640 Chapter 15 Multiple Regression 642 Statistics in Practice: dunnhumby 643 15. 1 Multiple Regression Model 644 Regression Model and Regression Equation 644 Estimated Multiple Regression Equation 644 15. Least Squares Method 645 An Example: Butler Trucking Company 646 Note on Interpretation of Coefficients 648 15. 3 Multiple Coefficient of Determination 654 15. 4 Model Assumptions 657 Contents xix 15. 5 Testing for Significance 658 F Test 658 t Test 661 Multicollinearity 662 15. 6 Using the Estimated Regression Equation for Estimation and Prediction 665 15. 7 Categorical Independent Variables 668 An Example: Johnson Filtration, Inc. 668 Interpreting the Parameters 670 More Complex Categorical Variables 672 15. 8 Residual Analysis 676 Detecting Outliers 678 Studentized Deleted Residuals and Outliers 678 Influential Observations 679 Using Cook’s Distance Measure to Identify Influential Observations 679 15. Logistic Regression 683 Logistic Regression Equation 684 Estimating the Logistic Regression Equation 685 Testing for Significance 687 Managerial Use 688 Interpreting the Logistic Regression Equation 688 Logit Transformation 691 Summary 694 Glossary 695 Key Formulas 696 Supplementary Exercises 698 Case Problem 1: Consumer Research, Inc. 704 Case Problem 2: Alumni Giving 705 Case Problem 3: PGA Tour Statistics 705 Case Problem 4: Predicting Winning Percentage for the NFL 708 Appendix 15. 1 Multiple Regression with Minitab 708 Appendix 15. 2 Multiple Regression with Excel 709 Appendix 15. 3 Logistic Regression with Minitab 710 Appendix 15. 4 Multiple Regression with StatTools 711Chapter 16 Regression Analysis: Model Buildi ng 712 Statistics in Practice: Monsanto Company 713 16. 1 General Linear Model 714 Modeling Curvilinear Relationships 714 Interaction 718 xx Contents Transformations Involving the Dependent Variable 720 Nonlinear Models That Are Intrinsically Linear 724 16. 2 Determining When to Add or Delete Variables 729 General Case 730 Use of p-Values 732 16. 3 Analysis of a Larger Problem 735 16. 4 Variable Selection Procedures 739 Stepwise Regression 739 Forward Selection 740 Backward Elimination 741 Best-Subsets Regression 741 Making the Final Choice 742 16. 5 Multiple Regression Approach to Experimental Design 745 16. Autocorrelation and the Durbin-Watson Test 750 Summary 754 Glossary 754 Key Formulas 754 Supplementary Exercises 755 Case Problem 1: Analysis of PGA Tour Statistics 758 Case Problem 2: Fuel Economy for Cars 759 Appendix 16. 1 Variable Selection Procedures with Minitab 760 Appendix 16. 2 Variable Selection Procedures with StatTools 761 Chapter 17 Index Numbers 763 Statistics in Practice: U. S. Department of Labor, Bureau of Labor Statistics 764 17. 1 Price Relatives 765 17. 2 Aggregate Price Indexes 765 17. 3 Computing an Aggregate Price Index from Price Relatives 769 17. 4 Some Important Price Indexes 771 Consumer Price Index 771 Producer Price Index 771 Dow Jones Averages 772 17. 5 Deflating a Series by Price Indexes 773 17. 6 Price Indexes: Other Considerations 777 Selection of Items 777 Selection of a Base Period 777 Quality Changes 777 17. Quantity Indexes 778 Summary 780 Contents xxi Glossary 780 Key Formulas 780 Supplementary Exercises 781 Chapter 18 Time Series Analysis and Forecasting 784 Statistics in Practice: Nevada Occupational Health Clinic 785 18. 1 Time Series Patterns 786 Horizontal Pattern 786 Trend Pattern 788 Seasonal Pattern 788 Trend and Seasonal Pattern 789 Cyclical Pattern 789 Selecting a Forecasting Method 791 18. 2 Forecast Accuracy 792 18. 3 Moving Averages and Exponential Smoothing 797 Moving Averages 797 Weighted Moving Average s 800 Exponential Smoothing 800 18. 4 Trend Projection 807 Linear Trend Regression 807 Holt’s Linear Exponential Smoothing 812 Nonlinear Trend Regression 814 18. Seasonality and Trend 820 Seasonality Without Trend 820 Seasonality and Trend 823 Models Based on Monthly Data 825 18. 6 Time Series Decomposition 829 Calculating the Seasonal Indexes 830 Deseasonalizing the Time Series 834 Using the Deseasonalized Time Series to Identify Trend 834 Seasonal Adjustments 836 Models Based on Monthly Data 837 Cyclical Component 837 Summary 839 Glossary 840 Key Formulas 841 Supplementary Exercises 842 Case Problem 1: Forecasting Food and Beverage Sales 846 Case Problem 2: Forecasting Lost Sales 847 Appendix 18. 1 Forecasting with Minitab 848 Appendix 18. 2 Forecasting with Excel 851 Appendix 18. 3 Forecasting with StatTools 852 xxii Contents Chapter 19 Nonparametric Methods 855 Statistics in Practice: West Shell Realtors 856 19. Sign Test 857 Hypothesis Test About a Population Median 857 Hypothesis Test with Matched Samples 862 19. 2 Wilcoxon Signed-Rank Test 865 19. 3 Mann-Whitney-Wilcoxon Test 871 19. 4 Kruskal-Wallis Test 882 19. 5 Rank Correlation 887 Summary 891 Glossary 892 Key Formulas 893 Supplementary Exercises 893 Appendix 19. 1 Nonparametric Methods with Minitab 896 Appendix 19. 2 Nonparametric Methods with Excel 899 Appendix 19. 3 Nonparametric Methods with StatTools 901 Chapter 20 Statistical Methods for Quality Control 903 Statistics in Practice: Dow Chemical Company 904 20. 1 Philosophies and Frameworks 905 Malcolm Baldrige National Quality Award 906 ISO 9000 906 Six Sigma 906 20. Statistical Process Control 908 Control Charts 909 _ x Chart: Process Mean and Standard Deviation Known 910 _ x Chart: Process Mean and Standard Deviation Unknown 912 R Chart 915 p Chart 917 np Chart 919 Interpretation of Control Charts 920 20. 3 Acceptance Sampling 922 KALI, Inc. : An Example of Acceptance Sampling 924 Computing the Probability of Accepting a Lot 924 Select ing an Acceptance Sampling Plan 928 Multiple Sampling Plans 930 Summary 931 Glossary 931 Key Formulas 932 Supplementary Exercises 933 Appendix 20. 1 Control Charts with Minitab 935 Appendix 20. 2 Control Charts with StatTools 935 Contents xxiii Chapter 21 Decision Analysis 937 Statistics in Practice: Ohio Edison Company 938 21. Problem Formulation 939 Payoff Tables 940 Decision Trees 940 21. 2 Decision Making with Probabilities 941 Expected Value Approach 941 Expected Value of Perfect Information 943 21. 3 Decision Analysis with Sample Information 949 Decision Tree 950 Decision Strategy 951 Expected Value of Sample Information 954 21. 4 Computing Branch Probabilities Using Bayes’ Theorem 960 Summary 964 Glossary 965 Key Formulas 966 Supplementary Exercises 966 Case Problem: Lawsuit Defense Strategy 969 Appendix: An Introduction to PrecisionTree 970 Chapter 22 Sample Survey On Website Statistics in Practice: Duke Energy 22-2 22. 1 Terminology Used in Sample Surveys 22-2 22. 2 Types of Surveys and Sampling Methods 22-3 22. Survey Errors 22-5 Nonsampling Error 22-5 Sampling Error 22-5 22. 4 Simple Random Sampling 22-6 Population Mean 22-6 Population Total 22-7 Population Proportion 22-8 Determining the Sample Size 22-9 22. 5 Stratified Simple Random Sampling 22-12 Population Mean 22-12 Population Total 22-14 Population Proportion 22-15 Determining the Sample Size 22-16 22. 6 Cluster Sampling 22-21 Population Mean 22-23 Population Total 22-24 Population Proportion 22-25 Determining the Sample Size 22-26 22. 7 Systematic Sampling 22-29 Summary 22-29 xxiv Contents Glossary 22-30 Key Formulas 22-30 Supplementary Exercises 22-34 Appendix: Self-Test Solutions and Answers to Even-Numbered Exercises 22-37Appendix A References and Bibliography 976 Appendix B Tables 978 Appendix C Summation Notation 1005 Appendix D Self-Test Solutions and Answers to Even-Numbered Exercises 1007 Appendix E Using Excel Functions 1062 Appendix F Computing p-Values Using Minitab and Exc el 1067 Index 1071 Preface The purpose of STATISTICS FOR BUSINESS AND ECONOMICS is to give students, primarily those in the fields of business administration and economics, a conceptual introduction to the field of statistics and its many applications. The text is applications oriented and written with the needs of the nonmathematician in mind; the mathematical prerequisite is knowledge of algebra.Applications of data analysis and statistical methodology are an integral part of the organization and presentation of the text material. The discussion and development of each technique is presented in an application setting, with the statistical results providing insights to decisions and solutions to problems. Although the book is applications oriented, we have taken care to provide sound methodological development and to use notation that is generally accepted for the topic being covered. Hence, students will find that this text provides good preparation for the study of more advanced statistical material. A bibliography to guide further study is included as an appendix.The text introduces the student to the software packages of Minitab 15 and Microsoft ® Office Excel 2007 and emphasizes the role of computer software in the application of statistical analysis. Minitab is illustrated as it is one of the leading statistical software packages for both education and statistical practice. Excel is not a statistical software package, but the wide availability and use of Excel make it important for students to understand the statistical capabilities of this package. Minitab and Excel procedures are provided in appendixes so that instructors have the flexibility of using as much computer emphasis as desired for the course.Changes in the Eleventh Edition We appreciate the acceptance and positive response to the previous editions of STATISTICS FOR BUSINESS AND ECONOMICS. Accordingly, in making modifications for this new edition, we have maintained the presentation style and readability of those editions. The significant changes in the new edition are summarized here. Content Revisions †¢ Revised Chapter 18 — â€Å"Time Series Analysis and Forecasting. † The chapter has been completely rewritten to focus more on using the pattern in a time series plot to select an appropriate forecasting method. We begin with a new Section 18. 1 on time series patterns, followed by a new Section 18. on methods for measuring forecast accuracy. Section 18. 3 discusses moving averages and exponential smoothing. Section 18. 4 introduces methods appropriate for a time series that exhibits a trend. Here we illustrate how regression analysis and Holt’s linear exponential smoothing can be used for linear trend projection, and then discuss how regression analysis can be used to model nonlinear relationships involving a quadratic trend and an exponential growth. Section 18. 5 then shows how dummy variables can be used to model seasonality in a foreca sting equation. Section 18. 6 discusses classical time series decomposition, including the concept of deseasonalizing a time series.There is a new appendix on forecasting using the Excel add-in StatTools and most exercises are new or updated. †¢ Revised Chapter 19 — â€Å"Nonparametric Methods. † The treatment of nonparametric methods has been revised and updated. We contrast each nonparametric method xxvi Preface †¢ †¢ †¢ †¢ †¢ †¢ †¢ †¢ with its parametric counterpart and describe how fewer assumptions are required for the nonparametric procedure. The sign test emphasizes the test for a population median, which is important in skewed populations where the median is often the preferred measure of central location. The Wilcoxon Rank-Sum test is used for both matched samples tests and tests about a median of a symmetric population.A new small-sample application of the Mann-Whitney-Wilcoxon test shows the exact sampling distrib ution of the test statistic and is used to explain why the sum of the signed ranks can be used to test the hypothesis that the two populations are identical. The chapter concludes with the Kruskal-Wallis test and rank correlation. New chapter ending appendixes describe how Minitab, Excel, and StatTools can be used to implement nonparametric methods. Twenty-seven data sets are now available to facilitate computer solution of the exercises. StatTools Add-In for Excel. Excel 2007 does not contain statistical functions or data analysis tools to perform all the statistical procedures discussed in the text.StatTools is a commercial Excel 2007 add-in, developed by Palisades Corporation, that extends the range of statistical options for Excel users. In an appendix to Chapter 1 we show how to download and install StatTools, and most chapters include a chapter appendix that shows the steps required to accomplish a statistical procedure using StatTools. We have been very careful to make the us e of StatTools completely optional so that instructors who want to teach using the standard tools available in Excel 2007 can continue to do so. But users who want additional statistical capabilities not available in standard Excel 2007 now have access to an industry standard statistics add-in that students will be able to continue to use in the workplace. Change in Terminology for Data.In the previous edition, nominal and ordinal data were classified as qualitative; interval and ratio data were classified as quantitative. In this edition, nominal and ordinal data are referred to as categorical data. Nominal and ordinal data use labels or names to identify categories of like items. Thus, we believe that the term categorical is more descriptive of this type of data. Introducing Data Mining. A new section in Chapter 1 introduces the relatively new field of data mining. We provide a brief overview of data mining and the concept of a data warehouse. We also describe how the fields of st atistics and computer science join to make data mining operational and valuable. Ethical Issues in Statistics.Another new section in Chapter 1 provides a discussion of ethical issues when presenting and interpreting statistical information. Updated Excel Appendix for Tabular and Graphical Descriptive Statistics. The chapter-ending Excel appendix for Chapter 2 shows how the Chart Tools, PivotTable Report, and PivotChart Report can be used to enhance the capabilities for displaying tabular and graphical descriptive statistics. Comparative Analysis with Box Plots. The treatment of box plots in Chapter 2 has been expanded to include relatively quick and easy comparisons of two or more data sets. Typical starting salary data for accounting, finance, management, and marketing majors are used to illustrate box plot multigroup comparisons. Revised Sampling Material.The introduction of Chapter 7 has been revised and now includes the concepts of a sampled population and a frame. The distincti on between sampling from a finite population and an infinite population has been clarified, with sampling from a process used to illustrate the selection of a random sample from an infinite population. A practical advice section stresses the importance of obtaining close correspondence between the sampled population and the target population. Revised Introduction to Hypothesis Testing. Section 9. 1, Developing Null and Alternative Hypotheses, has been revised. A better set of guidelines has been developed for identifying the null and alternative hypotheses.The context of the situation and the purpose for taking the sample are key. In situations in which the Preface xxvii †¢ †¢ †¢ †¢ focus is on finding evidence to support a research finding, the research hypothesis is the alternative hypothesis. In situations where the focus is on challenging an assumption, the assumption is the null hypothesis. New PrecisionTree Software for Decision Analysis. PrecisionTree is a nother Excel add-in developed by Palisades Corporation that is very helpful in decision analysis. Chapter 21 has a new appendix which shows how to use the PrecisionTree add-in. New Case Problems. We have added 5 new case problems to this edition, bringing the total number of case problems to 31.A new case problem on descriptive statistics appears in Chapter 3 and a new case problem on hypothesis testing appears in Chapter 9. Three new case problems have been added to regression in Chapters 14, 15, and 16. These case problems provide students with the opportunity to analyze larger data sets and prepare managerial reports based on the results of the analysis. New Statistics in Practice Applications. Each chapter begins with a Statistics in Practice vignette that describes an application of the statistical methodology to be covered in the chapter. New to this edition are Statistics in Practice articles for Oceanwide Seafood in Chapter 4 and the London-based marketing services company d unnhumby in Chapter 15. New Examples and Exercises Based on Real Data.We continue to make a significant effort to update our text examples and exercises with the most current real data and referenced sources of statistical information. In this edition, we have added approximately 150 new examples and exercises based on real data and referenced sources. Using data from sources also used by The Wall Street Journal, USA Today, Barron’s, and others, we have drawn from actual studies to develop explanations and to create exercises that demonstrate the many uses of statistics in business and economics. We believe that the use of real data helps generate more student interest in the material and enables the student to learn about both the statistical methodology and its application. The eleventh edition of the text contains over 350 examples and exercises based on real data.Features and Pedagogy Authors Anderson, Sweeney, and Williams have continued many of the features that appeare d in previous editions. Important ones for students are noted here. Methods Exercises and Applications Exercises The end-of-section exercises are split into two parts, Methods and Applications. The Methods exercises require students to use the formulas and make the necessary computations. The Applications exercises require students to use the chapter material in real-world situations. Thus, students first focus on the computational â€Å"nuts and bolts† and then move on to the subtleties of statistical application and interpretation. Self-Test ExercisesCertain exercises are identified as â€Å"Self-Test Exercises. † Completely worked-out solutions for these exercises are provided in Appendix D at the back of the book. Students can attempt the Self-Test Exercises and immediately check the solution to evaluate their understanding of the concepts presented in the chapter. Margin Annotations and Notes and Comments Margin annotations that highlight key points and provide ad ditional insights for the student are a key feature of this text. These annotations, which appear in the margins, are designed to provide emphasis and enhance understanding of the terms and concepts being presented in the text. xxviii PrefaceAt the end of many sections, we provide Notes and Comments designed to give the student additional insights about the statistical methodology and its application. Notes and Comments include warnings about or limitations of the methodology, recommendations for application, brief descriptions of additional technical considerations, and other matters. Data Files Accompany the Text Over 200 data files are available on the website that accompanies the text. The data sets are available in both Minitab and Excel formats. File logos are used in the text to identify the data sets that are available on the website. Data sets for all case problems as well as data sets for larger exercises are included. Acknowledgments A special thank you goes to Jeffrey D. Camm, University of Cincinnati, and James J.Cochran, Louisiana Tech University, for their contributions to this eleventh edition of Statistics for Business and Economics. Professors Camm and Cochran provided extensive input for the new chapters on forecasting and nonparametric methods. In addition, they provided helpful input and suggestions for new case problems, exercises, and Statistics in Practice articles. We would also like to thank our associates from business and industry who supplied the Statistics in Practice features. We recognize them individually by a credit line in each of the articles. Finally, we are also indebted to our senior acquisitions editor Charles McCormick, Jr. , our developmental editor Maggie Kubale, our content project manager, Jacquelyn K Featherly, our marketing manager Bryant T.Chrzan, and others at Cengage South-Western for their editorial counsel and support during the preparation of this text. David R. Anderson Dennis J. Sweeney Thomas A. Williams About the Authors David R. Anderson. David R. Anderson is Professor of Quantitative Analysis in the College of Business Administration at the University of Cincinnati. Born in Grand Forks, North Dakota, he earned his B. S. , M. S. , and Ph. D. degrees from Purdue University. Professor Anderson has served as Head of the Department of Quantitative Analysis and Operations Management and as Associate Dean of the College of Business Administration at the University of Cincinnati. In addition, he was the coordinator of the College’s first Executive Program.At the University of Cincinnati, Professor Anderson has taught introductory statistics for business students as well as graduate-level courses in regression analysis, multivariate analysis, and management science. He has also taught statistical courses at the Department of Labor in Washington, D. C. He has been honored with nominations and awards for excellence in teaching and excellence in service to student organizations. Profe ssor Anderson has coauthored 10 textbooks in the areas of statistics, management science, linear programming, and production and operations management. He is an active consultant in the field of sampling and statistical methods. Dennis J.Sweeney. Dennis J. Sweeney is Professor of Quantitative Analysis and Founder of the Center for Productivity Improvement at the University of Cincinnati. Born in Des Moines, Iowa, he earned a B. S. B. A. degree from Drake University and his M. B. A. and D. B. A. degrees from Indiana University, where he was an NDEA Fellow. During 1978–79, Professor Sweeney worked in the management science group at Procter & Gamble; during 1981–82, he was a visiting professor at Duke University. Professor Sweeney served as Head of the Department of Quantitative Analysis and as Associate Dean of the College of Business Administration at the University of Cincinnati.Professor Sweeney has published more than 30 articles and monographs in the area of managem ent science and statistics. The National Science Foundation, IBM, Procter & Gamble, Federated Department Stores, Kroger, and Cincinnati Gas & Electric have funded his research, which has been published in Management Science, Operations Research, Mathematical Programming, Decision Sciences, and other journals. Professor Sweeney has coauthored 10 textbooks in the areas of statistics, management science, linear programming, and production and operations management. Thomas A. Williams. Thomas A. Williams is Professor of Management Science in the College of Business at Rochester Institute of Technology.Born in Elmira, New York, he earned his B. S. degree at Clarkson University. He did his graduate work at Rensselaer Polytechnic Institute, where he received his M. S. and Ph. D. degrees. Before joining the College of Business at RIT, Professor Williams served for seven years as a faculty member in the College of Business Administration at the University of Cincinnati, where he developed th e undergraduate program in Information Systems and then served as its coordinator. At RIT he was the first chairman of the Decision Sciences Department. He teaches courses in management science and statistics, as well as graduate courses in regression and decision analysis.Professor Williams is the coauthor of 11 textbooks in the areas of management science, statistics, production and operations management, and mathematics. He has been a consultant for numerous Fortune 500 companies and has worked on projects ranging from the use of data analysis to the development of large-scale regression models. This page intentionally left blank STATISTICS FOR BUSINESS AND ECONOMICS 11e This page intentionally left blank CHAPTER Data and Statistics CONTENTS STATISTICS IN PRACTICE: BUSINESSWEEK 1. 1 APPLICATIONS IN BUSINESS AND ECONOMICS Accounting Finance Marketing Production Economics DATA Elements, Variables, and Observations Scales of Measurement Categorical and Quantitative Data Cross-Sectio nal and Time Series Data 1. DATA SOURCES Existing Sources Statistical Studies Data Acquisition Errors DESCRIPTIVE STATISTICS STATISTICAL INFERENCE COMPUTERS AND STATISTICAL ANALYSIS DATA MINING ETHICAL GUIDELINES FOR STATISTICAL PRACTICE 1 1. 4 1. 5 1. 6 1. 7 1. 8 1. 2 2 Chapter 1 Data and Statistics STATISTICS in PRACTICE NEW YORK, NEW YORK BUSINESSWEEK* With a global circulation of more than 1 million, BusinessWeek is the most widely read business magazine in the world. More than 200 dedicated reporters and editors in 26 bureaus worldwide deliver a variety of articles of interest to the business and economic community. Along with feature articles on current topics, the magazine contains regular sections on International Business, Economic Analysis, Information Processing, and Science & Technology.Information in the feature articles and the regular sections helps readers stay abreast of current developments and assess the impact of those developments on business and economic condit ions. Most issues of BusinessWeek provide an in-depth report on a topic of current interest. Often, the in-depth reports contain statistical facts and summaries that help the reader understand the business and economic information. For example, the February 23, 2009 issue contained a feature article about the home foreclosure crisis, the March 17, 2009 issue included a discussion of when the stock market would begin to recover, and the May 4, 2009 issue had a special report on how to make pay cuts less painful.In addition, the weekly BusinessWeek Investor provides statistics about the state of the economy, including production indexes, stock prices, mutual funds, and interest rates. BusinessWeek also uses statistics and statistical information in managing its own business. For example, an annual survey of subscribers helps the company learn about subscriber demographics, reading habits, likely purchases, lifestyles, and so on. BusinessWeek managers use statistical summaries from the survey to provide better services to subscribers and advertisers. One recent North *The authors are indebted to Charlene Trentham, Research Manager at BusinessWeek, for providing this Statistics in Practice. BusinessWeek uses statistical facts and summaries in many of its articles.  © Terri Miller/E-Visual Communications, Inc.American subscriber survey indicated that 90% of BusinessWeek subscribers use a personal computer at home and that 64% of BusinessWeek subscribers are involved with computer purchases at work. Such statistics alert BusinessWeek managers to subscriber interest in articles about new developments in computers. The results of the survey are also made available to potential advertisers. The high percentage of subscribers using personal computers at home and the high percentage of subscribers involved with computer purchases at work would be an incentive for a computer manufacturer to consider advertising in BusinessWeek. In this chapter, we discuss the types of d ata available for statistical analysis and describe how the data are obtained.We introduce descriptive statistics and statistical inference as ways of converting data into meaningful and easily interpreted statistical information. Frequently, we see the following types of statements in newspapers and magazines: †¢ The National Association of Realtors reported that the median price paid by firsttime home buyers is $165,000 (The Wall Street Journal, February 11, 2009). †¢ NCAA president Myles Brand reported that college athletes are earning degrees at record rates. Latest figures show that 79% of all men and women student-athletes graduate (Associated Press, October 15, 2008). †¢ The average one-way travel time to work is 25. 3 minutes (U. S. Census Bureau, March 2009). 1. 1 Applications in Business and Economics 3 †¢ A record high 11% of U. S. omes are vacant, a glut created by the housing boom and subsequent collapse (USA Today, February 13, 2009). †¢ The na tional average price for regular gasoline reached $4. 00 per gallon for the first time in history (Cable News Network website, June 8, 2008). †¢ The New York Yankees have the highest salaries in major league baseball. The total payroll is $201,449,289 with a median salary of $5,000,000 (USA Today Salary Data Base, April 2009). †¢ The Dow Jones Industrial Average closed at 8721 (The Wall Street Journal, June 2, 2009). The numerical facts in the preceding statements ($165,000, 79%, 25. 3, 11%, $4. 00, $201,449,289, $5,000,000 and 8721) are called statistics.In this usage, the term statistics refers to numerical facts such as averages, medians, percents, and index numbers that help us understand a variety of business and economic situations. However, as you will see, the field, or subject, of statistics involves much more than numerical facts. In a broader sense, statistics is defined as the art and science of collecting, analyzing, presenting, and interpreting data. Particul arly in business and economics, the information provided by collecting, analyzing, presenting, and interpreting data gives managers and decision makers a better understanding of the business and economic environment and thus enables them to make more informed and better decisions. In this text, we emphasize the use of statistics for business and economic decision making.Chapter 1 begins with some illustrations of the applications of statistics in business and economics. In Section 1. 2 we define the term data and introduce the concept of a data set. This section also introduces key terms such as variables and observations, discusses the difference between quantitative and categorical data, and illustrates the uses of cross-sectional and time series data. Section 1. 3 discusses how data can be obtained from existing sources or through survey and experimental studies designed to obtain new data. The important role that the Internet now plays in obtaining data is also highlighted. The uses of data in developing descriptive statistics and in making statistical inferences are described in Sections 1. 4 and 1. 5.The last three sections of Chapter 1 provide the role of the computer in statistical analysis, an introduction to the relative new field of data mining, and a discussion of ethical guidelines for statistical practice. A chapter-ending appendix includes an introduction to the add-in StatTools which can be used to extend the statistical options for users of Microsoft Excel. 1. 1 Applications in Business and Economics In today’s global business and economic environment, anyone can access vast amounts of statistical information. The most successful managers and decision makers understand the information and know how to use it effectively. In this section, we provide examples that illustrate some of the uses of statistics in business and economics. Accounting Public accounting firms use statistical sampling procedures when conducting audits for their clien ts.For instance, suppose an accounting firm wants to determine whether the amount of accounts receivable shown on a client’s balance sheet fairly represents the actual amount of accounts receivable. Usually the large number of individual accounts receivable makes reviewing and validating every account too time-consuming and expensive. As common practice in such situations, the audit staff selects a subset of the accounts called a sample. After reviewing the accuracy of the sampled accounts, the auditors draw a conclusion as to whether the accounts receivable amount shown on the client’s balance sheet is acceptable. 4 Chapter 1 Data and Statistics Finance Financial analysts use a variety of statistical information to guide their investment recommendations.In the case of stocks, the analysts review a variety of financial data including price/earnings ratios and dividend yields. By comparing the information for an individual stock with information about the stock market a verages, a financial analyst can begin to draw a conclusion as to whether an individual stock is over- or underpriced. For example, Barron’s (February 18, 2008) reported that the average dividend yield for the 30 stocks in the Dow Jones Industrial Average was 2. 45%. Altria Group showed a dividend yield of 3. 05%. In this case, the statistical information on dividend yield indicates a higher dividend yield for Altria Group than the average for the Dow Jones stocks. Therefore, a financial analyst might conclude that Altria Group was underpriced.This and other information about Altria Group would help the analyst make a buy, sell, or hold recommendation for the stock. Marketing Electronic scanners at retail checkout counters collect data for a variety of marketing research applications. For example, data suppliers such as ACNielsen and Information Resources, Inc. , purchase point-of-sale scanner data from grocery stores, process the data, and then sell statistical summaries of the data to manufacturers. Manufacturers spend hundreds of thousands of dollars per product category to obtain this type of scanner data. Manufacturers also purchase data and statistical summaries on promotional activities such as special pricing and the use of in-store displays.Brand managers can review the scanner statistics and the promotional activity statistics to gain a better understanding of the relationship between promotional activities and sales. Such analyses often prove helpful in establishing future marketing strategies for the various products. Production Today’s emphasis on quality makes quality control an important application of statistics in production. A variety of statistical quality control charts are used to monitor the output of a production process. In particular, an x-bar chart can be used to monitor the average output. Suppose, for example, that a machine fills containers with 12 ounces of a soft drink. Periodically, a production worker selects a sa mple of containers and computes the average number of ounces in the sample.This average, or x-bar value, is plotted on an x-bar chart. A plotted value above the chart’s upper control limit indicates overfilling, and a plotted value below the chart’s lower control limit indicates underfilling. The process is termed â€Å"in control† and allowed to continue as long as the plotted x-bar values fall between the chart’s upper and lower control limits. Properly interpreted, an x-bar chart can help determine when adjustments are necessary to correct a production process. Economics Economists frequently provide forecasts about the future of the economy or some aspect of it. They use a variety of statistical information in making such forecasts.For instance, in forecasting inflation rates, economists use statistical information on such indicators as the Producer Price Index, the unemployment rate, and manufacturing capacity utilization. Often these statistical ind icators are entered into computerized forecasting models that predict inflation rates. Applications of statistics such as those described in this section are an integral part of this text. Such examples provide an overview of the breadth of statistical applications. To supplement these examples, practitioners in the fields of business and economics provided chapter-opening Statistics in Practice articles that introduce the material covered in each chapter.The Statistics in Practice applications show the importance of statistics in a wide variety of business and economic situations. 1. 2 Data 5 1. 2 Data Data are the facts and figures collected, analyzed, and summarized for presentation and interpretation. All the data collected in a particular study are referred to as the data set for the study. Table 1. 1 shows a data set containing information for 25 mutual funds that are part of the Morningstar Funds500 for 2008. Morningstar is a company that tracks over 7000 mutual funds and pre pares in-depth analyses of 2000 of these. Their recommendations are followed closely by financial analysts and individual investors. Elements, Variables, and Observations Elements are the entities on which data are collected.For the data set in Table 1. 1 each individual mutual fund is an element: the element names appear in the first column. With 25 mutual funds, the data set contains 25 elements. A variable is a characteristic of interest for the elements. The data set in Table 1. 1 includes the following five variables: †¢ Fund Type: The type of mutual fund, labeled DE (Domestic Equity), IE (International Equity), and FI (Fixed Income) †¢ Net Asset Value ($): The closing price per share on December 31, 2007 TABLE 1. 1 DATA SET FOR 25 MUTUAL FUNDS 5-Year Expense Net Asset Average Ratio Morningstar Value ($) Return (%) (%) Rank 14. 37 10. 73 24. 94 16. 92 35. 73 13. 47 73. 1 48. 39 45. 60 8. 60 49. 81 15. 30 17. 44 27. 86 40. 37 10. 68 26. 27 53. 89 22. 46 37. 53 12. 10 2 4. 42 15. 68 32. 58 35. 41 30. 53 3. 34 10. 88 15. 67 15. 85 17. 23 17. 99 23. 46 13. 50 2. 76 16. 70 15. 31 15. 16 32. 70 9. 51 13. 57 23. 68 51. 10 16. 91 15. 46 4. 31 13. 41 2. 37 17. 01 13. 98 1. 41 0. 49 0. 99 1. 18 1. 20 0. 53 0. 89 0. 90 0. 89 0. 45 1. 36 1. 32 1. 31 1. 16 1. 05 1. 25 1. 36 1. 24 0. 80 1. 27 0. 62 0. 29 0. 16 0. 23 1. 19 3-Star 4-Star 3-Star 3-Star 4-Star 3-Star 5-Star 4-Star 3-Star 3-Star 4-Star 3-Star 5-Star 3-Star 2-Star 3-Star 4-Star 4-Star 4-Star 4-Star 3-Star 4-Star 3-Star 3-Star 4-Star Fund Name American Century Intl.Disc American Century Tax-Free Bond American Century Ultra Artisan Small Cap Brown Cap Small DFA U. S. Micro Cap Fidelity Contrafund Fidelity Overseas Fidelity Sel Electronics Fidelity Sh-Term Bond Gabelli Asset AAA Kalmar Gr Val Sm Cp Marsico 21st Century Mathews Pacific Tiger Oakmark I PIMCO Emerg Mkts Bd D RS Value A T. Rowe Price Latin Am. T. Rowe Price Mid Val Thornburg Value A USAA Income Vanguard Equity-Inc Vanguard Sht-Tm TE Vangua rd Sm Cp Idx Wasatch Sm Cp Growth Fund Type IE FI DE DE DE DE DE IE DE FI DE DE DE IE DE FI DE IE DE DE FI DE FI DE DE WEB file Morningstar Data sets such as Morningstar are available on the website for this text. Source: Morningstar Funds500 (2008). 6 Chapter 1Data and Statistics †¢ 5-Year Average Return (%): The average annual return for the fund over the past 5 years †¢ Expense Ratio: The percentage of assets deducted each fiscal year for fund expenses †¢ Morningstar Rank: The overall risk-adjusted star rating for each fund; Morningstar ranks go from a low of 1-Star to a high of 5-Stars Measurements collected on each variable for every element in a study provide the data. The set of measurements obtained for a particular element is called an observation. Referring to Table 1. 1 we see that the set of measurements for the first observation (American Century Intl. Disc) is IE, 14. 37, 30. 53, 1. 41, and 3-Star.The set of measurements for the second observation (Ameri can Century Tax-Free Bond) is FI, 10. 73, 3. 34, 0. 49, and 4-Star, and so on. A data set with 25 elements contains 25 observations. Scales of Measurement Data collection requires one of the following scales of measurement: nominal, ordinal, interval, or ratio. The scale of measurement determines the amount of information contained in the data and indicates the most appropriate data summarization and statistical analyses. When the data for a variable consist of labels or names used to identify an attribute of the element, the scale of measurement is considered a nominal scale. For example, referring to the data in Table 1. , we see that the scale of measurement for the Fund Type variable is nominal because DE, IE, and FI are labels used to identify the category or type of fund. In cases where the scale of measurement is nominal, a numeric code as well as nonnumeric labels may be used. For example, to facilitate data collection and to prepare the data for entry into a computer databa se, we might use a numeric code by letting 1 denote Domestic Equity, 2 deno