Question 1

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

Accepted Answer

A) True 
 B)False

Question 2

By selecting a larger alpha level,a researcher is ______.

Accepted Answer

A) attempting to make it easier to reject H0 
B) better able to detect a treatment effect 
C) increasing the risk of a Type I error 
D) All of the other options are the result of selecting a larger alpha level. 
A) attempting to make it easier to reject H0 
B) better able to detect a treatment effect 
C) increasing the risk of a Type I error 
D) All of the other options are the result of selecting a larger alpha level.

Question 3

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 
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 4

It is possible for a very small treatment effect to be a statistically significant treatment effect.

Accepted Answer

A) True 
 B)False

Question 5

A researcher administers a treatment to a sample from a population with a mean of µ = 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 would state that µ ≥ 60.

Accepted Answer

A) True 
 B)False

Question 6

A researcher would like to determine whether an over-the-counter cold medication has an effect on mental alertness.A sample of n = 16 participants is obtained,and each person is given a standard dose of the medication one hour before being tested in a driving simulation task.For the general population,scores on the simulation task are normally distributed with μ = 60 and σ = 8.The individuals in the sample had an average score of M = 56.5.
a.Can the researcher conclude that scores on the driving simulation task are significantly different after taking the medication? Use a two-tailed test with α = .05.
b.Can the researcher conclude that scores on the driving simulation task are significantly lower after taking the medication? Use a one-tailed test with α = .05.
c.Compute Cohen's d to measure the size of the effect.

Accepted Answer

a.H₀: µ = 60.With α = .05,the critical r

Question 7

There is always a possibility that the decision reached in a hypothesis test is incorrect.

Accepted Answer

A) True 
 B)False

Question 8

Under what circumstances can a very small treatment effect still be significant?

Accepted Answer

A) If the sample size (n) is very large 
B) If the sample standard deviation (?) is very large 
C) If the standard error of M (? M) is very large 
D) All of the other factors are likely to produce a significant result. 
A) If the sample size (n) is very large 
B) If the sample standard deviation (?) is very large 
C) If the standard error of M (? M) is very large 
D) All of the other factors are likely to produce a significant result.

Question 9

If all other factors are held constant,increasing the sample size from n = 25 to n = 100 will increase the power of a statistical test.

Accepted Answer

A) True 
 B)False

Question 10

Some researchers claim that herbal supplements such as ginseng or ginkgo biloba enhance human memory.To test this claim,a researcher selects a sample of n = 25 college students.Each student is given a ginkgo biloba supplement daily for six weeks and then all the participants are given a standardized memory test.For the population,scores on the test are normally distributed with μ = 70 and σ = 15.The sample of n = 25 students had a mean score of M = 75.
a.Are the data sufficient to say that the herb has a significant effect on memory? Use a two-tailed test with α = .05.
b.Compute Cohen's d for this study.

Accepted Answer

a.H₀: µ = 70 (students who take the herb

Question 11

If other factors are held constant,lowering the alpha level will increase the power of a hypothesis test.

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. 
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

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

Accepted Answer

A) True 
 B)False

Question 14

A researcher is evaluating a treatment that is expected to increase scores.If a one-tailed test with α = .05 is used,then the critical region consists of z-scores less than -1.65.

Accepted Answer

A) True 
 B)False

Question 15

If a hypothesis test produces a z-score in the critical region,what decision should be made?

Accepted Answer

A) Reject the alternative hypothesis 
B) Fail to reject the alternative hypothesis 
C) Reject the null hypothesis 
D) Fail to reject the null hypothesis 
A) Reject the alternative hypothesis 
B) Fail to reject the alternative hypothesis 
C) Reject the null hypothesis 
D) Fail to reject the null hypothesis

Question 16

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 
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 17

What is measured by the numerator of the z-score test statistic?

Accepted Answer

A) A likely distance between M and µ that would be expected if H0 was true 
B) The actual distance between M and µ 
C) The position of the sample mean relative to the critical region 
D) Whether or not there is a significant difference between M and µ 
A) A likely distance between M and µ that would be expected if H0 was true 
B) The actual distance between M and µ 
C) The position of the sample mean relative to the critical region 
D) Whether or not there is a significant difference between M and µ

Question 18

The critical boundaries for a hypothesis test are z = +1.96 and -1.96.If the z-score for the sample data is z = -1.90,what is the correct statistical decision?

Accepted Answer

A) Fail to reject H1 
B) Fail to reject H0 
C) Reject H1 
D) Reject H0 
A) Fail to reject H1 
B) Fail to reject H0 
C) Reject H1 
D) Reject H0

Question 19

A hypothesis test involves a comparison of which two elements?

Accepted Answer

A) Research results from a sample and a hypothesis about a population 
B) Research results from a population and a hypothesis about a sample 
C) Research results from a population and a hypothesis about the population 
D) Research results from a sample and a hypothesis about the sample 
A) Research results from a sample and a hypothesis about a population 
B) Research results from a population and a hypothesis about a sample 
C) Research results from a population and a hypothesis about the population 
D) Research results from a sample and a hypothesis about the sample

Question 20

What is measured by the denominator of the z-score test statistic?

Accepted Answer

A) A likely distance between M and µ that would be expected if H0 was true 
B) The actual distance between M and µ 
C) The position of the sample mean relative to the critical region 
D) Whether or not there is a significant difference between M and µ 
A) A likely distance between M and µ that would be expected if H0 was true 
B) The actual distance between M and µ 
C) The position of the sample mean relative to the critical region 
D) Whether or not there is a significant difference between M and µ

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

By selecting a larger alpha level,a researcher is ______.

What is the consequence of a Type II error?

It is possible for a very small treatment effect to be a statistically significant treatment effect.

A researcher administers a treatment to a sample from a population with a mean of µ = 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 would state that µ ≥ 60.

There is always a possibility that the decision reached in a hypothesis test is incorrect.

Under what circumstances can a very small treatment effect still be significant?

If all other factors are held constant,increasing the sample size from n = 25 to n = 100 will increase the power of a statistical test.

If other factors are held constant,lowering the alpha level will increase the power of a hypothesis test.

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

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

A researcher is evaluating a treatment that is expected to increase scores.If a one-tailed test with α = .05 is used,then the critical region consists of z-scores less than -1.65.

If a hypothesis test produces a z-score in the critical region,what decision should be made?

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

What is measured by the numerator of the z-score test statistic?

The critical boundaries for a hypothesis test are z = +1.96 and -1.96.If the z-score for the sample data is z = -1.90,what is the correct statistical decision?

A hypothesis test involves a comparison of which two elements?

What is measured by the denominator of the z-score test statistic?

Introduction to Statistics.

Frequency Distributions.

Central Tendency.

Variability.

z-Scores: Location of Scores and Standardized Distributions.

Probability.

Probability and Samples: The Distribution of Sample Means.

Introduction to the t Statistic

The t Test for Two Independent Samples

The t Test for Two Related Samples

Introduction to Analysis of Variance

Repeated-Measures and Two-Factor Analysis of Variance

Correlation and Regression.

The Chi-Square Statistic: Tests for Goodness of Fit and Independence

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Exam 8: Introduction to Hypothesis Testing.

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

By selecting a larger alpha level,a researcher is ______.

What is the consequence of a Type II error?

It is possible for a very small treatment effect to be a statistically significant treatment effect.

A researcher administers a treatment to a sample from a population with a mean of µ = 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 would state that µ ≥ 60.

There is always a possibility that the decision reached in a hypothesis test is incorrect.

Under what circumstances can a very small treatment effect still be significant?

If all other factors are held constant,increasing the sample size from n = 25 to n = 100 will increase the power of a statistical test.

If other factors are held constant,lowering the alpha level will increase the power of a hypothesis test.

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

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

A researcher is evaluating a treatment that is expected to increase scores.If a one-tailed test with α = .05 is used,then the critical region consists of z-scores less than -1.65.

If a hypothesis test produces a z-score in the critical region,what decision should be made?

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

What is measured by the numerator of the z-score test statistic?

The critical boundaries for a hypothesis test are z = +1.96 and -1.96.If the z-score for the sample data is z = -1.90,what is the correct statistical decision?

A hypothesis test involves a comparison of which two elements?

What is measured by the denominator of the z-score test statistic?

Introduction to Statistics.

Frequency Distributions.

Central Tendency.

Variability.

z-Scores: Location of Scores and Standardized Distributions.

Probability.

Probability and Samples: The Distribution of Sample Means.

Introduction to the t Statistic

The t Test for Two Independent Samples

The t Test for Two Related Samples

Introduction to Analysis of Variance

Repeated-Measures and Two-Factor Analysis of Variance

Correlation and Regression.

The Chi-Square Statistic: Tests for Goodness of Fit and Independence

Filters