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Solution Manual For Applied Statistics in Business and Economics 7th Edition By David Doane
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Solution Manual For Applied Statistics in Business and Economics 7th Edition By David Doane
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TEST BANK for Applied Statistics in Business and Economics 7th Edition by David Doane & Lori Seward. (All 18 Chapters)
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ASBE 7 e Solutions for Instructors 1 Solution Man ual For Applied Statistics in Business and Economics7th Edition By David Doane Chapter 1 Overview of Statistics 1.1 a. Statistics can be used to 1) dete rmine what a typical commission is and then 2) use that value to identify commissions that appear to be unusually high. b. She could use statistics to show the average energy use compared to previous models. She could also use statistics to show h ow durable the monitor would be in the field . c. He could use statistics to calculate the average absenteeism at each plant and then compare across the three plants. d. He could calculate average number of defects in each shipment. He could determine variation in number of defects between the three shipments. Learning Objective: 01-1 1.2 a. He could calculate the job turnover for each gender for each restaurant. He could then look at the difference between the various restaurants as well as the difference between genders. b. He could calculate the average number of emails received and sent for employees in different job classifications and make comparisons. c. The portfolio manager could calculate both the average return and the variation on return for the six different investments and make comparisons. d. By studying the busiest times of day for surgery, the administrator could work with surgeons to spread their surgeries out to better use the facilities. He might also look at which surgeries take the longest and which are shorter to help with scheduling. Learning Objective: 01-1 1.3 a. The average business school graduate should expect to use compute rs to manipulate the data. b. Answers will vary. Weak quantitative skills lead to poor decision making because data -based decision making is a hallmark of successful busine sses. If one cannot analyze data or understand summary analyses, one will be making decisions without full information. Learning Objective: 01-2 1.4 a. Answers will vary. W hy Not Study: It is difficult to become a statistical ―expert‖ after taking one introductory college course. A business person should hire statistical experts and h ave faith that those who are using statistics are doing it correctly. Why Study: In fact, most college graduates will use statistics every day. Relying on a con sultant to perform simple or even complex statistical analyses means turning over part of the 2 business decision -making to someone who doesn‘t know your business as well as you do. b. Answers will vary. Answers provided in part a will be similar for the s ubjects of accounting. Foreign languages are essential in this global business environment of today. While learning a foreign language can take considerably more time as an adult, the investment is worth it. Businesses are looking for college graduates tha t have quantitative skills and speak a foreign language. Chinese and Spanish are popular choices. c. To arrive at an absurd result, and then conclude the original assumption must have been wrong, since it gave us this absurd result. This is also known as proof by contradiction. It makes use of the law of excluded middle — a statement which cannot be false, must then be true. If you state that you will never use statistics in your business profession then you might conclude that you shouldn‘t study statistics. However, the original assumption of never using statistics is wrong ; therefore the conclusion of not needing to study statistics is also wrong. Learning Objective: 01-2 1.5 a. Answers will vary. b. An hour with an expert at the beginning of a project could be the smartest move a manager can make. A consultant is helpful w hen your team lacks certain critical skills, or when an unbiased or informed view cannot be found inside your organization. Expert consultants can handle domineering or indecisive team members, personality clashes, fears about adverse findings, and local politics. As in any business decision, the costs of paying for stat istical assistance must be weighed against the benefits. Costs are: statistician‘s time, more time invested in the beginning of a project which may mean results are not immediate. Benefits include: better sampling strategies which can result in more usefu l data, a better understanding of what information can be extracted from the data, greater confidence in the results. Learning Objective: 01-2 1.6 a. The ethical issue is that credit card companies are using unfair marketing practices to entic e students to use credit cards . Students are a vulnerable group that has not been educated about personal finance. Credit card companies are also purchasing student lists from universities and various student groups. This is also an unethical practice by the universities. b. They used an in -person survey given to 1500 students. These students were randomly solicited at popular places on campus. The sampling technique was a convenience sample. The report did not attempt to make inferences about the popu lation of college students. The report simply provided statistics collected from their sample. The naïve reader would most likely make the inference that the numbers from the sample apply to the population as a whole. This should be made clearer in the rep ort. c. The subjects surveyed include 1) how students pay for their education, 2) how they use credit cards, 3) how many of them use credit cards, and 4) attitudes toward credit card marketing on campus. It would be interesting to see what the questions were and how they were worded. d. Because the survey focused on students‘ opinions and did not provide information about credit card use by the general population it is difficult to conclude that the marketing 3 practices companies use on campuses are dif ferent from those used to market cards to the general public. Furthermore, it was not obvious that those students who had credit cards obtained those cards as a direct result of the campus marketing efforts. What was impressive was the amount of research t he group did to support their claims of unethical practices. The references to other reports and court cases were a better support for their claims in question 1. e. Answers vary. In general, because the study was based on a convenience sample the result s cannot be assumed to hold for the general population of students. Also, it would be good to know how students‘ use of credit cards compares to the general public. f. The list of sc hools included in the survey is focused in a few states such as Massach usetts, California, and Colorado. There were very few schools from the southeast and virtually no private colleges or universities. Because it was a convenience sample it is not appropriate to extend the results from the survey to the larger population of college students. However, many of the references cited did suggest that the problem was widespread. g. First, they suggest eliminating "freebies" or gifts that would entice students to sign up for a credit card. Second, they suggest limiting posted mar keting materials on campus. The third solution is to disallow acquisition of students ‘ lists. Fourth, they suggest that sponsorship should be discontinued. In other words, credit card companies cannot pay for student groups to get them new customers. Th e fifth recommendation is to enhance student awareness about credit card problems. Finally, they suggest that certain terms that take advantage of students should be discouraged. For example, hidden fees, changing contracts, and universal default should be eliminated . As a follow up to this report note that the Credit Card Accountability Responsibility and Disclosure Act of 2009 or Credit CARD Act of 2009 is a federal law passe d by the United States Congress and signed by President Barack Obama on May 22, 2009. It is comprehensive credit card reform legislation that aims "...to establish fair and transparent practices relating to the extension of credit under an open end consumer credit plan, and for other purposes."[1] Learning Objective : 01-3 1.7 Answers will vary. Examples include: linking expectations on conduct to the company‘s mission, explaining what is considered acceptable and unacceptable behavi or, providing courses of action for employees when they have questions or believe an ethical guideline has been violated, documentation so that employees will know the code, addressing nepotism, addressing romantic relationships, addressing customer relati onships and vendor relationships. Learning Objective: 01-3 1.8 Mary is falling for Pitfall 3: Conclusions from Rare Events. Just because an event is unlikely doesn‘t mean it will never happen. The probability may be small but there is a chance of observing the same five winning numbers in the same sequence on two different days. Learning Objective: 01-4 1.9 Bob is falling for Pitfall 5: Assuming a Causal Link. Statistical association does not prove causation. Bob also appears to be falling for Pitfall 6: Generalization to Individuals. 4 Even if there were a link between cell phones and binge drinking, the link would be between groups of cell phone users and groups of binge drinkers, not necessarily a one to one link. Learning Objective: 01-4 1.10 a. It is not obvious that there is a direct cause and effect relationship between an individual choosing to use a radar detector and that individual choosing to vote and wear a seatbelt. b. Increasing the use of radar detectors may not influence those who o bey laws and are less concerned with government limitations. Learning Objective: 01-4 1.11 a. No, the met hod did not ―work‖ in the sense that he increased his chances of winning by picking the numbers the way he did . Every combination of six nu mbers has the same chance of winning. The fact that this winner chose his numbers based on his families‘ birthdays and school grade does not increase the chance of him winning. b. Someone who picks 1 -2-3-4-5-6 has just as much chance of winning as anyone else (see (a)). Learning Objective: 01-4 1.12 a. The phrase ―much more‖ is not quantified. The study report is not mentioned. There is no way to determine the veracity of this statement. Six causes of car accidents could be poor weather, road construction, heavy traffic, inexperienced driver, engine fail ure, and drinking. Smoking is not on this list. b. Smokers might pay less attention to driving when lighting a cigarette. Learning Objective: 01-4 1.13 The percent reduction might not seem important because it appears so small but when multiplied by millions of calls each day it does translate into a significant improvement . Learning Objective: 01-4 1.14 a. The conclusion was a broad generalization . This can cause ethical issues if action was taken against employee s that had legitimate complaints about management decisions . b. The sample is too small , and non-random, creating bias. c. This test is only going to be performed in the laboratory which limits the ability to see how it works out in the world. Additionally, there is no informed consent. d. The sample is once again way too small and is non random. This again creates bias which creates no ca usal link. Learning Objective: 01-4 1.15 Sarah‘s statement is not correct. Most people would feel the difference is practically important. 0.9% of 231,164 is 2,080 patients. Learning Objective: 01-4 1.16 The headline implies causation but we cannot assume causation just because the repeal came before the increase in deaths. The deaths could have been going up each year before this study or there could be other variables contributing to the increase in deaths.
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