Exam (elaborations) TEST BANK FOR Introduction to the Practice of Statistics 9TH Edition By David S. Moore, George P. McCabe, Bruce Craig ( Solution Manual)

1.1. Most students will prefer to work in seconds, to avoid having to work with decimals or fractions. 1.2. Who? The individuals in the data set are students in a statistics class. What? There are eight variables: ID (a label, with no units); Exam1, Exam2, Homework, Final, and Project (in units in “points,” scaled from 0 to 100); TotalPoints (in points, computed from the other scores, on a scale of 0 to 900); and Grade (A, B, C, D, and E). Why? The primary purpose of the data is to assign grades to the students in this class, and (presumably) the variables are appropriate for this purpose. (The data might also be useful for other purposes.) 1.3. Exam1 = 79, Exam2 = 88, Final = 88. 1.4. For this student, TotalPoints = 2 · 86+2 · 82+3 · 77+2 · 90+80 = 827, so the grade is B. 1.5. The cases are apartments. There are five variables: rent (quantitative), cable (categorical), pets (categorical), bedrooms (quantitative), distance to campus (quantitative). 1.6. (a) To find injuries per worker, divide the rates in Example 1.6 by 100,000 (or, redo the computations without multiplying by 100,000). For wage and salary workers, there are 0. fatal injuries per worker. For self-employed workers, there are 0. fatal injuries per worker. (b) These rates are 1/10 the size of those in Example 1.6, or 10,000 times larger than those in part (a): 0.34 fatal injuries per 10,000 wage/salary workers, and 0.99 fatal injuries per 10,000 self-employed workers. (c) The rates in Example 1.6 would probably be more easily understood by most people, because numbers like 3.4 and 9.9 feel more “familiar.” (It might be even better to give rates per million worker: 34 and 99.) 1.7. Shown are two possible stemplots; the first uses split stems (described on page 11 of the text). The scores are slightly left-skewed; most range from 70 to the low 90s. 5 58 6 0 6 58 7 0023 7 5558 8 00003 8 5557 9 9 8 5 58 6 058 7 8 9 1.8. Preferences will vary. However, the stemplot in Figure 1.8 shows a bit more detail, which is useful for comparing the two distributions. 1.9. (a) The stemplot of the altered data is shown on the right. (b) Blank stems should always be retained (except at the beginning or end of the stemplot), because the gap in the distribution is an important piece of information about the data. 1 6 22 5568 3 34 3 55678 4 4 8 5 1 53 54 Chapter 1 Looking at Data—Distributions 1.10. Student preferences will vary. The stemplot has the advantage of showing each individual score. Note that this histogram has the same shape as the second histogram in Exercise 1.7. 100 0 1 2 3 4 5 6 7 8 9 Frequency First exam scores 1.11. Student preferences may vary, but the larger classes in this histogram hide a lot of detail. 0 2 4 6 8 10 12 14 16 18 Frequency First exam scores 1.12. This histogram shows more details about the distribution (perhaps more detail than is useful). Note that this histogram has the same shape as the first histogram in the solution to Exercise 1.7. 0 1 2 3 4 5 6 7 Frequency First exam scores 1.13. Using either a stemplot or histogram, we see that the distribution is left-skewed, centered near 80, and spread from 55 to 98. (Of course, a histogram would not show the exact values of the maximum and minimum.) 1.14. (a) The cases are the individual employees. (b) The first four (employee identification number, last name, first name, and middle initial) are labels. Department and education level are categorical variables; number of years with the company, salary, and age are quantitative variables. (c) Column headings in student spreadsheets will vary, as will sample cases. 1.15. A Web search for “city rankings” or “best cities” will yield lots of ideas, such as crime rates, income, cost of living, entertainment and cultural activities, taxes, climate, and school system quality. (Students should be encouraged to think carefully about how some of these might be quantitatively measured.) Solutions 55 1.16. Recall that categorical variables place individuals into groups or categories, while quantitative variables “take numerical values for which arithmetic operations. . . make sense.” Variables (a), (d), and (e)—age, amount spent on food, and height—are quantitative. The answers to the other three questions—about dancing, musical instruments, and broccoli—are categorical variables. 1.18. Student answers will vary. A Web