Question 1

A sample of n = 16 individuals is selected from a population with μ = 60 and σ = 6 and a treatment is administered to the sample.After treatment, the sample mean is M = 63.What is the value of Cohen's d for this sample?

Accepted Answer

A) 0.33 
B) 0.50 
C) 2.00 
D) 3.00

Question 2

Which of the following correctly describes the effect of increasing the alpha level (for example from .01 to .05)?

Accepted Answer

A) increase the likelihood of rejecting H0 and increase the risk of a Type I error 
B) decrease the likelihood of rejecting H0 and increase the risk of a Type I error 
C) increase the likelihood of rejecting H0 and decrease the risk of a Type I error 
D) decrease the likelihood of rejecting H0 and decrease the risk of a Type I error

Question 3

Which of the following accurately describes the effect of increasing the alpha level?

Accepted Answer

A) increases the standard error and has no effect on the risk of a Type I error 
B) decreases the standard error and has no effect on the risk of a Type I error 
C) increases the risk of a Type I error and has no effect on the standard error 
D) decreases the risk of a Type I error and has no effect on the standard error

Question 4

A researcher administers a treatment to a sample from a population with a mean of $\mu$ = 60.If the treatment is expected to increase scores and a one-tailed test is used to evaluate the treatment effect, then the null hypothesis states that $\mu$ $\geq$ 60.

Accepted Answer

A) True 
 B)False

Question 5

Which of the following is an accurate definition for the power of a statistical test?

Accepted Answer

A) the probability of rejecting a true null hypothesis 
B) the probability of supporting true null hypothesis 
C) the probability of rejecting a false null hypothesis 
D) the probability of supporting a false null hypothesis

Question 6

The alpha level determines the risk of a Type I error.

Accepted Answer

A) True 
 B)False

Question 7

Which of the following accurately describes the effect of increasing the sample size?

Accepted Answer

A) increases the standard error and has no effect on the risk of a Type I error 
B) decreases the standard error and has no effect on the risk of a Type I error 
C) increases the risk of a Type I error and has no effect on the standard error 
D) decreases the risk of a Type I error and has no effect on the standard error

Question 8

A Type I error occurs when a researcher concludes that a treatment has an effect but, in fact, the treatment has no effect.

Accepted Answer

A) True 
 B)False

Question 9

A researcher conducts a hypothesis test to evaluate the effect of a treatment that is expected to increase scores.The hypothesis test produces a z-score of z = 2.37.If the researcher is using a one-tailed test, what is the correct statistical decision?

Accepted Answer

A) Reject the null hypothesis with α = .05 but not with α = .01. 
B) Reject the null hypothesis with either α = .05 or α = .01. 
C) Fail to reject the null hypothesis with either α = .05 or α = .01. 
D) cannot answer without additional information

Question 10

The value obtained for Cohen's d is independent of the sample size.

Accepted Answer

A) True 
 B)False

Question 11

You can reduce the risk of a Type I error by using a larger sample.

Accepted Answer

A) True 
 B)False

Question 12

What is the relationship between the alpha level, the size of the critical region, and the risk of a Type I error?

Accepted Answer

A) As the alpha level increases, the size of the critical region increases and the risk of a Type I error increases. 
B) As the alpha level increases, the size of the critical region increases and the risk of a Type I error decreases. 
C) As the alpha level increases, the size of the critical region decreases and the risk of a Type I error increases. 
D) As the alpha level increases, the size of the critical region decreases and the risk of a Type I error decreases.

Question 13

What is the consequence of a Type II error?

Accepted Answer

A) concluding that a treatment has an effect when it really does 
B) concluding that a treatment has no effect when it really has no effect 
C) concluding that a treatment has no effect when it really does 
D) concluding that a treatment has an effect when it really has no effect

Question 14

A researcher conducts a hypothesis test to evaluate the effect of a treatment.The hypothesis test produces a z-score of z = 2.37.Assuming that the researcher is using a two-tailed test, what decision should be made?

Accepted Answer

A) The researcher should reject the null hypothesis with α = .05 but not with α = .01. 
B) The researcher should reject the null hypothesis with either α = .05 or α = .01. 
C) The researcher should fail to reject H0 with either α = .05 or α = .01. 
D) Cannot answer without additional information.

Question 15

If other factors are held constant, the larger the size of the treatment effect, the greater the power of the hypothesis test.

Accepted Answer

A) True 
 B)False

Question 16

A researcher administers a treatment to a sample of participants selected from a population with µ = 80.If a hypothesis test is used to evaluate the effect of the treatment, which combination of factors is most likely to result in rejecting the null hypothesis?

Accepted Answer

A) a sample mean near 80 for a small sample 
B) a sample mean near 80 for a large sample 
C) a sample mean much different than 80 for a small sample 
D) a sample mean much different than 80 for a large sample

Question 17

If the research prediction is that the treatment will decrease scores, then the critical region for a directional test will be in the left?hand tail.

Accepted Answer

A) True 
 B)False

Question 18

A researcher administers a treatment to a sample of n = 16 selected from a population with $\mu$ = 40 and $\sigma$ = 8.If the sample mean after treatment is M = 42, then Cohen's d = 1.00.

Accepted Answer

A) True 
 B)False

Question 19

If other factors are held constant, then increasing the sample size will increase the likelihood of rejecting the null hypothesis.

Accepted Answer

A) True 
 B)False

Question 20

When is there a risk of a Type II error?

Accepted Answer

A) whenever H0 is rejected 
B) whenever H1 is rejected 
C) whenever the decision is "fail to reject H0" 
D) The risk of a Type II error is independent of the decision from a hypothesis test.

Exam 8: Introduction to Hypothesis Testing

A sample of n = 16 individuals is selected from a population with μ = 60 and σ = 6 and a treatment is administered to the sample.After treatment, the sample mean is M = 63.What is the value of Cohen's d for this sample?

Which of the following correctly describes the effect of increasing the alpha level (for example from .01 to .05) ?

Which of the following accurately describes the effect of increasing the alpha level?

A researcher administers a treatment to a sample from a population with a mean of $\mu$ = 60.If the treatment is expected to increase scores and a one-tailed test is used to evaluate the treatment effect, then the null hypothesis states that $\mu$ $\geq$ 60.

Which of the following is an accurate definition for the power of a statistical test?

The alpha level determines the risk of a Type I error.

Which of the following accurately describes the effect of increasing the sample size?

A Type I error occurs when a researcher concludes that a treatment has an effect but, in fact, the treatment has no effect.

A researcher conducts a hypothesis test to evaluate the effect of a treatment that is expected to increase scores.The hypothesis test produces a z-score of z = 2.37.If the researcher is using a one-tailed test, what is the correct statistical decision?

The value obtained for Cohen's d is independent of the sample size.

You can reduce the risk of a Type I error by using a larger sample.

What is the relationship between the alpha level, the size of the critical region, and the risk of a Type I error?

What is the consequence of a Type II error?

A researcher conducts a hypothesis test to evaluate the effect of a treatment.The hypothesis test produces a z-score of z = 2.37.Assuming that the researcher is using a two-tailed test, what decision should be made?

If other factors are held constant, the larger the size of the treatment effect, the greater the power of the hypothesis test.

A researcher administers a treatment to a sample of participants selected from a population with µ = 80.If a hypothesis test is used to evaluate the effect of the treatment, which combination of factors is most likely to result in rejecting the null hypothesis?

If the research prediction is that the treatment will decrease scores, then the critical region for a directional test will be in the left?hand tail.

A researcher administers a treatment to a sample of n = 16 selected from a population with $\mu$ = 40 and $\sigma$ = 8.If the sample mean after treatment is M = 42, then Cohen's d = 1.00.

If other factors are held constant, then increasing the sample size will increase the likelihood of rejecting the null hypothesis.

When is there a risk of a Type II error?

Exam 8: Introduction to Hypothesis Testing

A sample of n = 16 individuals is selected from a population with μ = 60 and σ = 6 and a treatment is administered to the sample.After treatment, the sample mean is M = 63.What is the value of Cohen's d for this sample?

Which of the following correctly describes the effect of increasing the alpha level (for example from .01 to .05) ?

Which of the following accurately describes the effect of increasing the alpha level?

A researcher administers a treatment to a sample from a population with a mean of μ\muμ = 60.If the treatment is expected to increase scores and a one-tailed test is used to evaluate the treatment effect, then the null hypothesis states that μ\muμ ≥\geq≥ 60.

Which of the following is an accurate definition for the power of a statistical test?

The alpha level determines the risk of a Type I error.

Which of the following accurately describes the effect of increasing the sample size?

A Type I error occurs when a researcher concludes that a treatment has an effect but, in fact, the treatment has no effect.

A researcher conducts a hypothesis test to evaluate the effect of a treatment that is expected to increase scores.The hypothesis test produces a z-score of z = 2.37.If the researcher is using a one-tailed test, what is the correct statistical decision?

The value obtained for Cohen's d is independent of the sample size.

You can reduce the risk of a Type I error by using a larger sample.

What is the relationship between the alpha level, the size of the critical region, and the risk of a Type I error?

What is the consequence of a Type II error?

A researcher conducts a hypothesis test to evaluate the effect of a treatment.The hypothesis test produces a z-score of z = 2.37.Assuming that the researcher is using a two-tailed test, what decision should be made?

If other factors are held constant, the larger the size of the treatment effect, the greater the power of the hypothesis test.

A researcher administers a treatment to a sample of participants selected from a population with µ = 80.If a hypothesis test is used to evaluate the effect of the treatment, which combination of factors is most likely to result in rejecting the null hypothesis?

If the research prediction is that the treatment will decrease scores, then the critical region for a directional test will be in the left?hand tail.

A researcher administers a treatment to a sample of n = 16 selected from a population with μ\muμ = 40 and σ\sigmaσ = 8.If the sample mean after treatment is M = 42, then Cohen's d = 1.00.

If other factors are held constant, then increasing the sample size will increase the likelihood of rejecting the null hypothesis.

When is there a risk of a Type II error?

A researcher administers a treatment to a sample from a population with a mean of $\mu$ = 60.If the treatment is expected to increase scores and a one-tailed test is used to evaluate the treatment effect, then the null hypothesis states that $\mu$ $\geq$ 60.

A researcher administers a treatment to a sample of n = 16 selected from a population with $\mu$ = 40 and $\sigma$ = 8.If the sample mean after treatment is M = 42, then Cohen's d = 1.00.