1. © 2013 Pearson Education, Inc. Active Learning Lecture Slides For use with Classroom Response Systems Essential Statistics: Exploring the World through Data, 1e by Gould and Ryan Chapter 9: Inferring Population Means Slide 9 - 1

2. © 2013 Pearson Education, Inc. True or False The accuracy of an estimator is measured by the standard error. A.True B.False Slide 9 - 2

3. © 2013 Pearson Education, Inc. True or False The accuracy of an estimator is measured by the standard error. A.True B.False Slide 9 - 3

4. © 2013 Pearson Education, Inc. True or False The precision of an estimator is measured by the bias. A.True B.False Slide 9 - 4

5. © 2013 Pearson Education, Inc. True or False The precision of an estimator is measured by the bias. A.True B.False Slide 9 - 5

6. © 2013 Pearson Education, Inc. True or False A sampling distribution is a probability distribution of a statistic. A.True B.False Slide 9 - 6

7. © 2013 Pearson Education, Inc. True or False A sampling distribution is a probability distribution of a statistic. A.True B.False Slide 9 - 7

8. © 2013 Pearson Education, Inc. True or False When a statistic of the sampling distribution is the same value as the population parameter, we say that the statistic is an unbiased estimator. A.True B.False Slide 9 - 8

9. © 2013 Pearson Education, Inc. True or False When a statistic of the sampling distribution is the same value as the population parameter, we say that the statistic is an unbiased estimator. A.True B.False Slide 9 - 9

10. © 2013 Pearson Education, Inc. True or False The standard deviation of the sampling distribution is what we call the standard error. A.True B.False Slide 9 - 10

11. © 2013 Pearson Education, Inc. True or False The standard deviation of the sampling distribution is what we call the standard error. A.True B.False Slide 9 - 11

12. © 2013 Pearson Education, Inc. True or False The standard error of the sample mean, gets smaller with larger sample size. A.True B.False Slide 9 - 12

13. © 2013 Pearson Education, Inc. True or False The standard error of the sample mean, gets smaller with larger sample size. A.True B.False Slide 9 - 13

14. © 2013 Pearson Education, Inc. True or False For all populations, the sample mean is unbiased when estimating the population mean. A.True B.False Slide 9 - 14

15. © 2013 Pearson Education, Inc. True or False For all populations, the sample mean is unbiased when estimating the population mean. A.True B.False Slide 9 - 15

16. © 2013 Pearson Education, Inc. True or False When considering the sampling distribution of the sample mean, the larger the sample size, n, the better the approximation. A.True B.False Slide 9 - 16

17. © 2013 Pearson Education, Inc. True or False When considering the sampling distribution of the sample mean, the larger the sample size, n, the better the approximation. A.True B.False Slide 9 - 17

18. © 2013 Pearson Education, Inc. True or False When considering the sampling distribution of the sample mean, if the population is Normal to begin with, then the sampling distribution is exactly a Normal distribution. A.True B.False Slide 9 - 18

19. © 2013 Pearson Education, Inc. True or False When considering the sampling distribution of the sample mean, if the population is Normal to begin with, then the sampling distribution is exactly a Normal distribution. A.True B.False Slide 9 - 19

20. © 2013 Pearson Education, Inc. The sample mean is A.the arithmetic average of a sample of data B.an estimate of a population mean C.unbiased, if the sample is a random sample D.all of the above Slide 9 - 20

21. © 2013 Pearson Education, Inc. The sample mean is A.the arithmetic average of a sample of data B.an estimate of a population mean C.unbiased, if the sample is a random sample D.all of the above Slide 9 - 21

22. © 2013 Pearson Education, Inc. The t-distributions are A.symmetric B.unimodal C.“bell-shaped” D.all of the above Slide 9 - 22

23. © 2013 Pearson Education, Inc. The t-distributions are A.symmetric B.unimodal C.“bell-shaped” D.all of the above Slide 9 - 23

24. © 2013 Pearson Education, Inc. Compared to the z-distribution, the t-distribution has A.thinner tails B.thicker tails C.taller peaks D.more peaks Slide 9 - 24

25. © 2013 Pearson Education, Inc. Compared to the z-distribution, the t-distribution has A.thinner tails B.thicker tails C.taller peaks D.more peaks Slide 9 - 25

26. © 2013 Pearson Education, Inc. The t-distribution’s shape depends on only one parameter, called the A.mean B.standard deviation C.degrees of freedom D.all of the above Slide 9 - 26

27. © 2013 Pearson Education, Inc. The t-distribution’s shape depends on only one parameter, called the A.mean B.standard deviation C.degrees of freedom D.all of the above Slide 9 - 27

28. © 2013 Pearson Education, Inc. True or False Ultimately, when df is infinitely large, the t-distribution is exactly the same as the N(0, 1) distribution. A.True B.False Slide 9 - 28

29. © 2013 Pearson Education, Inc. True or False Ultimately, when df is infinitely large, the t-distribution is exactly the same as the N(0, 1) distribution. A.True B.False Slide 9 - 29

30. © 2013 Pearson Education, Inc. True or False Confidence intervals are a technique for communicating an estimate of the mean along with a measure of our uncertainty in that estimate. A.True B.False Slide 9 - 30

31. © 2013 Pearson Education, Inc. True or False Confidence intervals are a technique for communicating an estimate of the mean along with a measure of our uncertainty in that estimate. A.True B.False Slide 9 - 31

32. © 2013 Pearson Education, Inc. True or False A confidence interval can be interpreted as a range of plausible values for the population parameter. A.True B.False Slide 9 - 32

33. © 2013 Pearson Education, Inc. True or False A confidence interval can be interpreted as a range of plausible values for the population parameter. A.True B.False Slide 9 - 33

34. © 2013 Pearson Education, Inc. True or False The confidence level is a measure of how well the method used to produce the confidence interval performs. A.True B.False Slide 9 - 34

35. © 2013 Pearson Education, Inc. True or False The confidence level is a measure of how well the method used to produce the confidence interval performs. A.True B.False Slide 9 - 35

36. © 2013 Pearson Education, Inc. Which of the following are way(s) in which we can report a confidence interval? A.(lower boundary, upper boundary) B.Estimate ± margin of error C.Mean ± standard deviation D.both A and B above Slide 9 - 36

37. © 2013 Pearson Education, Inc. Which of the following are way(s) in which we can report a confidence interval? A.(lower boundary, upper boundary) B.Estimate ± margin of error C.Mean ± standard deviation D.both A and B above Slide 9 - 37

38. © 2013 Pearson Education, Inc. True or False Hypotheses are always statements about population statistics. A.True B.False Slide 9 - 38

39. © 2013 Pearson Education, Inc. True or False Hypotheses are always statements about population statistics. A.True B.False Slide 9 - 39

40. © 2013 Pearson Education, Inc. Which of the following value(s) for the significance level α are good choice(s)? A.0.01 B.0.05 C.0.10 D.all of the above Slide 9 - 40

41. © 2013 Pearson Education, Inc. Which of the following value(s) for the significance level α are good choice(s)? A.0.01 B.0.05 C.0.10 D.all of the above Slide 9 - 41

42. © 2013 Pearson Education, Inc. True or False The t-statistic measures how far away (how many standard errors) our observed mean,, lies from the true population value μ. A.True B.False Slide 9 - 42

43. © 2013 Pearson Education, Inc. True or False The t-statistic measures how far away (how many standard errors) our observed mean,, lies from the true population value μ. A.True B.False Slide 9 - 43

44. © 2013 Pearson Education, Inc. True or False In hypothesis testing, values of the t-statistic that are far from 0 tend to discredit the null hypothesis. A.True B.False Slide 9 - 44

45. © 2013 Pearson Education, Inc. True or False In hypothesis testing, values of the t-statistic that are far from 0 tend to discredit the null hypothesis. A.True B.False Slide 9 - 45

46. © 2013 Pearson Education, Inc. True or False The p-value tells us the probability that we would get a t-statistic as extreme as or more extreme than what we observed. A.True B.False Slide 9 - 46

47. © 2013 Pearson Education, Inc. True or False The p-value tells us the probability that we would get a t-statistic as extreme as or more extreme than what we observed. A.True B.False Slide 9 - 47

48. © 2013 Pearson Education, Inc. There are three basic pairs of hypotheses. The two-tailed one-sample t-test has the following hypotheses: A.H 0 : μ = μ 0 and H a : μ < μ 0 B.H 0 : μ = μ 0 and H a : μ ≠ μ 0 C.H 0 : μ = μ 0 and H a : μ > μ 0 D.H 0 : μ ≠ μ 0 and H a : μ = μ 0 Slide 8 - 48

49. © 2013 Pearson Education, Inc. There are three basic pairs of hypotheses. The two-tailed one-sample t-test has the following hypotheses: A.H 0 : μ = μ 0 and H a : μ < μ 0 B.H 0 : μ = μ 0 and H a : μ ≠ μ 0 C.H 0 : μ = μ 0 and H a : μ > μ 0 D.H 0 : μ ≠ μ 0 and H a : μ = μ 0 Slide 8 - 49

50. © 2013 Pearson Education, Inc. There are three basic pairs of hypotheses. The one-tailed (left) one-sample t-test has the following hypotheses: A.H 0 : μ = μ 0 and H a : μ < μ 0 B.H 0 : μ = μ 0 and H a : μ ≠ μ 0 C.H 0 : μ = μ 0 and H a : μ > μ 0 D.H 0 : μ ≠ μ 0 and H a : μ = μ 0 Slide 8 - 50

51. © 2013 Pearson Education, Inc. There are three basic pairs of hypotheses. The one-tailed (left) one-sample t-test has the following hypotheses: A.H 0 : μ = μ 0 and H a : μ < μ 0 B.H 0 : μ = μ 0 and H a : μ ≠ μ 0 C.H 0 : μ = μ 0 and H a : μ > μ 0 D.H 0 : μ ≠ μ 0 and H a : μ = μ 0 Slide 8 - 51

52. © 2013 Pearson Education, Inc. There are three basic pairs of hypotheses. The one-tailed (right) one-sample t-test has the following hypotheses: A.H 0 : μ = μ 0 and H a : μ < μ 0 B.H 0 : μ = μ 0 and H a : μ ≠ μ 0 C.H 0 : μ = μ 0 and H a : μ > μ 0 D.H 0 : μ ≠ μ 0 and H a : μ = μ 0 Slide 8 - 52

53. © 2013 Pearson Education, Inc. There are three basic pairs of hypotheses. The one-tailed (right) one-sample t-test has the following hypotheses: A.H 0 : μ = μ 0 and H a : μ < μ 0 B.H 0 : μ = μ 0 and H a : μ ≠ μ 0 C.H 0 : μ = μ 0 and H a : μ > μ 0 D.H 0 : μ ≠ μ 0 and H a : μ = μ 0 Slide 8 - 53

54. © 2013 Pearson Education, Inc. When comparing two populations, if the data sampled from the populations are one sample of related pairs, then the samples are A.independent samples B.paired (dependent) samples C.paired-independent samples D.not random samples Slide 9 - 54

55. © 2013 Pearson Education, Inc. When comparing two populations, if the data sampled from the populations are one sample of related pairs, then the samples are A.independent samples B.paired (dependent) samples C.paired-independent samples D.not random samples Slide 9 - 55

56. © 2013 Pearson Education, Inc. True or False With paired (dependent) samples, if you know the value that a subject has in one group, then you know something about the other group, too. A.True B.False Slide 9 - 56

57. © 2013 Pearson Education, Inc. True or False With paired (dependent) samples, if you know the value that a subject has in one group, then you know something about the other group, too. A.True B.False Slide 9 - 57

58. © 2013 Pearson Education, Inc. Which of the following are example(s) of when dependence occurs? A.“before and after” comparisons B.when the objects are related somehow (comparing twins, siblings, or spouses) C.when the experimenters have deliberately matched subjects in the groups to have similar characteristics D.all of the above Slide 9 - 58

59. © 2013 Pearson Education, Inc. Which of the following are example(s) of when dependence occurs? A.“before and after” comparisons B.when the objects are related somehow (comparing twins, siblings, or spouses) C.when the experimenters have deliberately matched subjects in the groups to have similar characteristics D.all of the above Slide 9 - 59

60. © 2013 Pearson Education, Inc. True or False With paired samples, we turn two samples into one. We do this by finding the difference in each pair. A.True B.False Slide 9 - 60

61. © 2013 Pearson Education, Inc. True or False With paired samples, we turn two samples into one. We do this by finding the difference in each pair. A.True B.False Slide 9 - 61