GRAVETTER CH.9

12. A sample of n = 16 scores has a mean of M = 65 and an estimated standard error of 2 points. What is the sample variance? a. s2 = 64 c. s2 = 16 b. s2 = 36 d. s2 = 4

A

13. Which set of characteristics will produce the smallest value for the estimated standard error? a. A large sample size and a small sample variance b. A large sample size and a large sample variance c. A small sample size and a small sample variance d. A small sample size and a large sample variance

A

16. A researcher conducts a hypothesis test using a sample of n = 20 from an unknown population. What is the df value for the t statistic? a. 19 b. 20 c. 21 d. Cannot be determined from the information given

A

1. Which of the following is a fundamental difference between the t statistic and a z-score? a. The t statistic uses the sample mean in place of the population mean. b. The t statistic uses the sample variance in place of the population variance. c. The t statistic computes the standard error by dividing the standard deviation by n - 1 instead of dividing by n. d. All of these are differences between t and z.

B

10. A sample of n = 25 scores has a mean of M = 40 and a standard deviation of s = 10. What is the estimated standard error for the sample mean? a. 4 c. 2.5 b. 2 d. 1

B

23. A hypothesis test produces a t statistic of t = 2.20. If the researcher is using a two-tailed test with α = .05, how large does the sample have to be in order to reject the null hypothesis? a. At least n = 11 c. At least n = 13 b. At least n = 12 d. At least n = 14

C

38. A sample is selected from a population with μ = 46, and a treatment is administered to the sample. After treatment, the sample mean is M = 48 with a sample variance of s2 = 16. Based on this information, what is the value of Cohen's d? a. d = 0.125 b. d = 0.25 c. d = 0.50 d. Cohen's d cannot be computed without knowing the sample size.

C

42. If a sample of n = 16 scores is being used to make an 80% confidence interval estimate of the population mean, μ, what value(s) of t should be used? a. t = 0 c. t = ±1.753 b. t = ±2.131 d. t = ±1.341

D

25. If the null hypothesis states that m = 70 and a researcher obtains a sample with M = 73 and s2 = 9, then Cohen's d = 0.33.

F

4. If two samples from the same population are the same size and have the same mean, then they will have the same t statistic.

F

7. A random sample with n = 20 scores has df = 19.

T

20. A researcher is using a two-tailed hypothesis test with α = .05 to evaluate the effect of a treatment. If the boundaries for the critical region are t = ± 2.080, then how many individuals are in the sample? a. n = 22 b. n = 21 c. n = 20 d. Impossible to determine without more information

A

6. A sample of n = 4 scores has SS = 60. What is the variance for this sample? a. 30 c. 16 b. 20 d. 15

B

14. Which of the following samples will have the smallest value for the estimated standard error? a. n = 4 with s2 = 16 c. n = 16 with s2 = 16 b. n = 4 with s2 = 64 d. n = 16 with s2 = 64

C

10. As the sample size is increased, the distribution of t statistics becomes flatter and more spread out.

F

24. A research report states "t(8) = 2.00, p > .05." For this test, r2 = 2/10.

F

1. When the population variance or standard deviation is not known, you must use a t statistic instead of a z-score for a hypothesis test.

T

11. For a hypothesis test using a t statistic, the boundaries for the critical region will change if the sample size is changed.

T

3. Compared to a z-score, a hypothesis test with a t statistic requires less information from the population.

T

11. A sample with a mean of M = 40 and a variance of s2 = 20 has an estimated standard error of 1 point. How many scores are in the sample? a. 4 c. 20 b. 5 d. 21

C

26. If other factors are held constant, what is the effect of increasing the sample size? a. It will increase the estimated standard error and increase the likelihood of rejecting H0. b. It will increase the estimated standard error and decrease the likelihood of rejecting H0. c. It will decrease the estimated standard error and increase the likelihood of rejecting H0. d. It will decrease the estimated standard error and decrease the likelihood of rejecting H0.

C

28. If other factors are held constant, which set of sample characteristics is most likely to reject a null hypothesis stating that μ = 80? a. M = 85 and small sample variance c. M = 90 and small sample variance b. M = 85 and large sample variance d. M = 90 and large sample variance

C

39. A sample is selected from a population with μ = 70, and a treatment is administered to the sample. After treatment, the sample mean is M = 74, and Cohen's d is d = 1.00. What is the value of the sample variance? a. s2 = 2 b. s2 = 4 c. s2 = 16 d. It is impossible to determine the sample variance without more information.

C

12. For a two-tailed test with α = .05 and a sample of n = 16, the boundaries for the critical region are t = ±2.120.

F

31. Under what circumstances can a very small treatment effect be statistically significant? a. If the sample size big and the sample variance is small b. If the sample size and the sample variance are both big c. If the sample size is small and the sample variance is big d. If the sample size and the sample variance are both small

A

33. A researcher selects a sample from a population with μ = 30 and uses the sample to evaluate the effect of a treatment. After treatment, the sample has a mean of M = 32 and a variance of s2 = 6. If Cohen's d is used to measure the size of the treatment effect, which of the following would have no effect on the value of Cohen's d? a. Increase the sample size b. Increase the sample mean c. Increase the sample variance d. All of the other options will influence the value of Cohen's d.

A

40. Which of the following describes what a confidence interval does? a. It uses a sample mean to estimate the corresponding population mean. b. It uses a population mean to predict a sample mean. c. It uses a level of confidence to estimate a sample mean. d. It uses the sample mean to determine a level of confidence.

A

45. Which of the following would have no effect on the width of a confidence interval? a. Increase the sample mean c. Increase the percentage of confidence b. Increase the size of the sample d. Increase the sample variance

A

50. With α = .05, what is the critical t value for a one-tailed test with n = 15? a. t = 1.761 c. t = 2.145 b. t = 1.753 d. t = 2.131

A

7. On average, what value is expected for the t statistic when the null hypothesis is true? a. t = 0 c. t = 1.96 b. t = 1 d. t > 1.96

A

17. When n is small (less than 30), how does the shape of the t distribution compare to the normal distribution? a. It is almost perfectly normal. b. It is flatter and more spread out than the normal distribution. c. It is taller and narrower than the normal distribution. d. There is no consistent relationship between the t distribution and the normal distribution.

B

19. With α = .05 and df = 8, the critical values for a two-tailed t test are t = ±2.306. Assuming all other factors are held constant, if the df value were increased to df = 20, what would happen to the critical values for t? a. They would increase in magnitude (move farther from zero). b. They would decrease in magnitude (move closer to zero). c. They would not change. d. Impossible to determine without more information

B

2. Which of the following is not needed to compute a t statistic? a. A hypothesized value for the population mean b. The value of the population variance or standard deviation c. The value of the sample mean d. The value of the sample variance or standard deviation

B

27. If other factors are held constant, what is the effect of increasing the sample variance? a. It will increase the estimated standard error and increase the likelihood of rejecting H0. b. It will increase the estimated standard error and decrease the likelihood of rejecting H0. c. It will decrease the estimated standard error and increase the likelihood of rejecting H0. d. It will decrease the estimated standard error and decrease the likelihood of rejecting H0.

B

3. Why are t statistics more variable than z-scores? a. The extra variability is caused by variations in the sample mean. b. The extra variability is caused by variations in the sample variance. c. The extra variability is caused by variations in the df value. d. None of the other options explains the extra variability for t statistics.

B

32. How does sample variance influence the estimated standard error and measures of effect size such as r2 and Cohen's d? a. Larger variance increases both the standard error and measures of effect size. b. Larger variance increases the standard error but decreases measures of effect size. c. Larger variance decreases the standard error but increases measures of effect size. d. Larger variance decreases both the standard error and measures of effect size.

B

34. Two samples from the same population both have M = 84 and s2 = 20, but one sample has n = 10 and the other has n = 20 scores. Both samples are used to evaluate a hypothesis stating that μ = 80 and to compute Cohen's d. How will the outcomes for the two samples compare? a. The larger sample is more likely to reject the hypothesis and will produce a larger value for Cohen's d. b. The larger sample is more likely to reject the hypothesis, but the two samples will have the same value for Cohen's d. c. The larger sample is less likely to reject the hypothesis and will produce a larger value for Cohen's d. d. The larger sample is less likely to reject the hypothesis, but the two samples will have the same value for Cohen's d.

B

36. If other factors are held constant, how does sample size influence the likelihood of rejecting the null hypothesis and measures of effect size such as r2 and Cohen's d? a. A larger sample increases both the likelihood and measures of effect size. b. A larger sample increases the likelihood but has little influence on measures of effect size. c. A larger sample decreases the likelihood but has little influence on measures of effect size. d. A larger sample decreases both the likelihood and measures of effect size.

B

41. What value is estimated with a confidence interval using the t statistic? a. The value for an unknown sample mean b. The value for an unknown population mean c. The difference between two population means d. The difference between two sample means

B

47. Which of the following is the correct way to report the results of a hypothesis test and a measure of effect size using a t statistic? a. t(19) = 2.30, r2 = 0.42, p < .05 c. r2 = 0.42, t(19) = 2.30 , p < .05 b. t(19) = 2.30, p < .05, r2 = 0.42, d. t = 2.30, df = 19, p < .05, r2 = 0.42

B

49. A hypothesis test with a sample of n = 25 participants produces a t statistic of t = +2.53. Assuming a one-tailed test with the critical region in the right-hand tail, what is the correct decision? a. The researcher can reject the null hypothesis with α = .05 but not with α = .01. b. The researcher can reject the null hypothesis with either α = .05 or α = .01. c. The researcher must fail to reject the null hypothesis with either α = .05 or α = .01. d. It is impossible to make a decision about H0 without more information.

B

8. What is the sample variance and the estimated standard error for a sample of n = 9 scores with SS = 72? a. s2 = 9 and sM = 3 c. s2 = 3 and sM = 3 b. s2 = 9 and sM = 1 d. s2 = 3 and sM = 1

B

9. A sample of n = 9 scores has a variance of s2 = 36. What is the estimated standard error for the sample mean? a. 1 c. 4 b. 2 d. 16

B

15. A researcher conducts a hypothesis test using a sample from an unknown population. If the t statistic has df = 30, how many individuals were in the sample? a. n = 29 b. n = 30 c. n = 31 d. Cannot be determined from the information given

C

18. With α = .01, the two-tailed critical region for a t test using a sample of n = 16 subjects would have boundaries of ______. a. t = ±2.602 c. t = ±2.947 b. t = ±2.583 d. t = ±2.921

C

22. A sample of n = 25 scores produces a t statistic of t = 2.062. If the researcher is using a two-tailed test, which of the following is the correct statistical decision? a. The researcher can reject the null hypothesis with α = .05 but not with α = .01. b. The researcher can reject the null hypothesis with either α = .05 or α = .01. c. The researcher must fail to reject the null hypothesis with either α = .05 or α = .01. d. It is impossible to make a decision about H0 without more information.

C

24. Two samples from the same population both have n = 10 scores with M = 45. If the t statistic is computed for each sample, then what is the relationship between the two t values? a. The two t statistics will be identical. b. The sample with the larger variance will produce the larger t statistic. c. The sample with the smaller variance will produce the larger t statistic. d. There is no way to predict the relationship between the two t statistics.

C

25. If other factors are held constant, which set of sample characteristics is most likely to produce a significant t statistic? a. n = 25 with s2 = 100 c. n = 100 with s2 = 100 b. n = 25 with s2 = 400 d. n = 100 with s2 = 400

C

43. A sample of n = 4 scores is selected from a population with an unknown mean. The sample has a mean of M = 40 and a variance of s2 = 16. Which of the following is the correct 90% confidence interval for μ? a. μ = 40 ± 2.353(4) c. μ = 40 ± 2.353(2) b. μ = 40 ± 1.638(4) d. μ = 40 ± 1.638(2)

C

44. Which combination of factors would definitely increase the width of a confidence interval? a. Increase the sample mean and increase the sample size b. Decrease the sample mean and increase the sample size c. Increase the sample mean and increase the percentage of confidence d. Decrease the sample mean and decrease the percentage of confidence

C

46. The results of a hypothesis test are reported as follows: t(15) = 2.70, p < .05. Based on this report, how many individuals were in the sample? a. 14 b. 15 c. 16 d. Cannot be determined from the information provided

C

48. A researcher selects a sample from a population with a mean of m = 40 and administers a treatment to the individuals in the sample. If the treatment is expected to decrease scores, which of the following is the correct statement of the null hypothesis for a one-tailed test? a. m > 40 c. m > 40 b. m < 40 d. m < 40

C

21. A sample has a mean of M = 39.5 and a standard deviation of s = 4.3, and produces a t statistic of t = 2.14. For a two-tailed hypothesis test with α = .05, what is the correct statistical decision for this sample? a. The researcher can reject the null hypothesis with α = .05 but not with α = .01. b. The researcher can reject the null hypothesis with either α = .05 or α = .01. c. The researcher must fail to reject the null hypothesis with either α = .05 or α = .01. d. It is impossible to make a decision about H0 without more information.

D

29. A researcher selects a sample from a population with μ = 30 and uses the sample to evaluate the effect of a treatment. After treatment, the sample has a mean of M = 32 and a variance of s2 = 6. Which of the following would definitely increase the likelihood of rejecting the null hypothesis? a. Increase the sample size b. Increase the sample mean c. Decrease the sample variance d. All of the other options will increase the likelihood of rejecting the null hypothesis.

D

30. If other factors are held constant, which set of sample characteristics is most likely to reject a null hypothesis stating that μ = 80? a. M = 85 for a sample of n = 25 c. M = 90 for a sample of n = 25 b. M = 85 for a sample of n = 100 d. M = 90 for a sample of n = 100

D

35. A sample of n = 16 scores produces a t statistic of t = 2.00. If the sample is used to measure effect size with r2, what value will be obtained for r2? a. r2 = 2/20 c. r2 = 2/19 b. r2 = 4/20 d. r2 = 4/19

D

37. If other factors are held constant, how does sample variance influence the likelihood of rejecting the null hypothesis and measures of effect size such as r2 and Cohen's d? a. Larger sample variance increases both the likelihood and measures of effect size. b. Larger sample variance increases the likelihood but has little influence on measures of effect size. c. Larger sample variance decreases the likelihood but has little influence on measures of effect size. d. Larger sample variance decreases both the likelihood and measures of effect size.

D

4. If a researcher is using a t statistic to test a null hypothesis about a population, what information is needed from the population to calculate the t statistic? a. You must know the population mean. b. You must know the population variance or standard deviation. c. You must know the population mean and the variance or standard deviation. d. The t statistic does not require any information about the population.

D

5. If two samples are selected from the same population, under what circumstances will the two samples have exactly the same t statistic? a. The samples are the same size and have the same variance b. The samples are the same size and have the same mean c. The samples have the same mean and the same variance d. The samples are the same size and have the same mean and the same variance

D

18. In general, the larger the value of the sample variance, the greater the likelihood of rejecting the null hypothesis.

F

20. In a hypothesis test, a large value for the sample variance increases the likelihood that you will find a significant treatment effect.

F

6. A sample of n = 16 scores with a sample variance of s2 = 64 has an estimated standard error of 4 points.

F

9. For a two-tailed hypothesis test with α = .05 and a sample of n = 25 scores, the boundaries for the critical region are t = ±2.060.

F

13. For a one-tailed test with α = .05 and a sample of n = 9, the critical value for the t statistic is t = 1.860.

T

14. The t distribution for df = 4 is flatter and more spread out than the t distribution for df = 20.

T

15. If two samples, each with n = 20 scores, are selected from the same population and both have the same mean (M = 53) and the same variance (s2 = 12), then they will also have the same t statistic.

T

16. If other factors are held constant, as the sample size increases, the estimated standard error decreases.

T

17. If other factors are held constant, as the sample variance increases, the estimated standard error also increases.

T

19. If other factors are held constant, the bigger the sample is, the greater the likelihood of rejecting the null hypothesis.

T

2. Compared to a z-score, a hypothesis test with a t statistic requires more information from the sample.

T

21. If a hypothesis test using a sample of n = 16 scores produces a t statistic of t = 2.15, then the correct decision is to reject the null hypothesis for a two-tailed test with α = .05.

T

23. A research report states "t(15) = 2.31, p < .05." For this study, the sample had n = 16 scores.

T

26. Although hypothesis tests are affected by sample size, sample size has little or no influence on measures of effect size, such as r2 or Cohen's d.

T

27. To estimate a population mean with a confidence interval, you first must estimate a range of values for t.

T

28. The sample mean will always be exactly in the center of a confidence interval that is estimating the value of the population mean.

T

29. If the 90% confidence interval for µ is from 40 to 50, then the sample mean is M = 45.

T

30. For a one-tailed test evaluating a treatment that is supposed to decrease scores, a researcher obtains t(8) = -1.90. For α = .05, the correct decision is to reject the null hypothesis.

T

5. A sample of n = 4 scores with SS = 48 has a variance of s2 = 16 and an estimated standard error of 2.

T

8. As sample size increases, the critical region boundaries for a two-tailed t-test with α = .05 will move closer to zero.

T

Two samples are selected from a population, and a treatment is administered to the samples. If both samples have the same mean and the same variance, you are more likely to find a significant treatment effect with a sample of n = 100 than with a sample of n = 4.

T