5.8: Chapter 5 Solutions
- Page ID
- 79037
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1.
- \(10\)
- \(\frac{10}{8}\)
3. \(N(10, \frac{10}{8}))\)
5. 0.7799
7. 1.675
9. Mean = 25, standard deviation = 2/7
10. Mean = 48, standard deviation = 5/6
11. Mean = 90, standard deviation = 3/4
12. Mean = 120, standard deviation = 0.38
13. Mean = 17, standard deviation = 0.17
14. Expected value = 17, standard deviation = 0.05
15. Expected value = 38, standard deviation = 0.43
16. Expected value = 14, standard deviation = 0.65
17. 0.999
18. 0.901
19. 0.301
20. 0.832
21. 0.483
22. 0.500
23. 0.502
24. 0.519
25.
- \(X\) = amount of change students carry
- \(X \sim N(0.88, 0.31)\)
- \(\overline x\) = average amount of change carried by a sample of 25 students.
- \(\overline x \sim N(0.88, 0.176)\)
- \(0.0819\)
- \(0.1882\)
- The distributions are different. Part 1 is normal for individual observations and part 2 is normal for sample means.
27.
- length of time for an individual to complete \(IRS\) form 1040, in hours.
- mean length of time for a sample of 36 taxpayers to complete \(IRS\) form 1040, in hours.
- \(N(10.53, \frac{1}{3})\)
- Yes. I would be surprised, because the probability is almost 0.
- No. I would not be totally surprised because the probability is 0.2296.
29.
- the length of a song, in minutes, in the collection
- \(N(2, 0.43)\)
- the average length, in minutes, of the songs from a sample of five albums from the collection
- \(N(2.75, 0.066)\)
- 2.706 minutes
- 0.088 minutes
31.
- True. The mean of a sampling distribution of the means is approximately the mean of the data distribution.
- True. According to the Central Limit Theorem, the larger the sample, the closer the sampling distribution of the means becomes normal.
- The standard deviation of the sampling distribution of the means will decrease as the sample size increases.
33.
- \(X\) = the yearly income of someone in a third world country
- the average salary from samples of 1,000 residents of a third world country
- \(\overline x \sim N\left(2000, \frac{8000}{\sqrt{1000}}\right)\)
- Very wide differences in data values can have averages smaller than standard deviations.
- The distribution of the sample mean will have higher probabilities closer to the population mean.
\(P(2000 < \overline x < 2100) = 0.1537 \)
\(P(2100 < \overline x < 2200) = 0.1317\)
35. b
36. 64
37.
- Yes
- Yes
- Yes
- 0.6
38. 400
39. 2.5
40. 25
41. 0.955
42. 0.927
43. 0.648
44. 0.101
45. 0.273