Question 1

Increasing the alpha level (for example from α = .01 to α = .05) _____.

Accepted Answer

A) increases the probability of a Type I error 
B) increases the size of the critical region 
C) increases the probability that the sample will fall into the critical region 
D) All of the other options are results of increasing alpha. 
A) increases the probability of a Type I error 
B) increases the size of the critical region 
C) increases the probability that the sample will fall into the critical region 
D) All of the other options are results of increasing alpha. D

Question 2

In general, the null hypothesis states that the treatment has no effect on the population mean.

Accepted Answer

A) True 
 B)False  True

Question 3

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  True

Question 4

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

Accepted Answer

A) True 
 B)False

Question 5

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 with α = .05 
B) a sample mean near 80 with α = .01 
C) a sample mean much different than 80 with α = .05 
D) a sample mean much different than 80 with α = .01 
A) a sample mean near 80 with α = .05 
B) a sample mean near 80 with α = .01 
C) a sample mean much different than 80 with α = .05 
D) a sample mean much different than 80 with α = .01

Question 6

The power of a hypothesis test is the probability that the sample mean will be in the critical region if the treatment has an effect.

Accepted Answer

A) True 
 B)False

Question 7

A Type I error occurs when a treatment actually does have an effect on the scores but the effect was not large enough to reject the null hypothesis.

Accepted Answer

A) True 
 B)False

Question 8

If a hypothesis test is found to have power = 0.70, then what is the probability that the test will result in a Type II error?

Accepted Answer

A) 0.30 
B) 0.70 
C) p > 0.70 
D) Cannot be determined without more information. 
A) 0.30 
B) 0.70 
C) p > 0.70 
D) Cannot be determined without more information.

Question 9

Which of the following is an accurate definition of a Type II error?

Accepted Answer

A) rejecting a false null hypothesis 
B) rejecting a true null hypothesis 
C) failing to reject a false null hypothesis 
D) failing to reject a true null hypothesis 
A) rejecting a false null hypothesis 
B) rejecting a true null hypothesis 
C) failing to reject a false null hypothesis 
D) failing to reject a true null hypothesis

Question 10

Which of the following is an accurate definition of a Type I error?

Accepted Answer

A) rejecting a false null hypothesis 
B) rejecting a true null hypothesis 
C) failing to reject a false null hypothesis 
D) failing to reject a true null hypothesis 
A) rejecting a false null hypothesis 
B) rejecting a true null hypothesis 
C) failing to reject a false null hypothesis 
D) failing to reject a true null hypothesis

Question 11

A researcher is conducting an experiment to evaluate a treatment that is expected to increase the scores for individuals in a population.If the researcher uses a one-tailed test with $\alpha$ = .01, then which of the following correctly identifies the critical region?

Accepted Answer

A) z > 2.33 B) z > 2.58 C) z < 2.33 D) z < 2.58 A) z > 2.33 B) z > 2.58 C) z < 2.33 D) z < 2.58

Question 12

Even if a treatment has no effect it is still possible to obtain an extreme sample mean that is very different from the population mean.What outcome is likely if this happens?

Accepted Answer

A) reject H0 and make a Type I error 
B) correctly reject H0 
C) fail to reject H0 and make a Type II error 
D) correctly fail to reject H0 
A) reject H0 and make a Type I error 
B) correctly reject H0 
C) fail to reject H0 and make a Type II error 
D) correctly fail to reject H0

Question 13

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, then 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 14

Which of the following will increase the power of a statistical test?

Accepted Answer

A) Change α from .05 to .01. 
B) Change from a one?tailed test to a two?tailed test. 
C) Change the sample size from n = 25 to n = 100. 
D) None of the other options will increase power. 
A) Change α from .05 to .01. 
B) Change from a one?tailed test to a two?tailed test. 
C) Change the sample size from n = 25 to n = 100. 
D) None of the other options will increase power.

Question 15

In a research report, the notation p < .05 indicates that the probability of a Type I error is less than .05.

Accepted Answer

A) True 
 B)False

Question 16

The critical region for a hypothesis test consists of sample outcomes that are very unlikely to occur if the null hypothesis is true.

Accepted Answer

A) True 
 B)False

Question 17

In a hypothesis test, the value obtained for the z-score is independent of the sample size.

Accepted Answer

A) True 
 B)False

Question 18

A sample of n = 25 individuals is selected from a population with µ = 80 and a treatment is administered to the sample.What is expected if the treatment has no effect?

Accepted Answer

A) The sample mean should be very different from 80 and should lead you to reject the null hypothesis. 
B) The sample mean should be very different from 80 and should lead you to fail to reject the null hypothesis. 
C) The sample mean should be close to 80 and should lead you to reject the null hypothesis. 
D) The sample mean should be close 80 and should lead you to fail to reject the null hypothesis. 
A) The sample mean should be very different from 80 and should lead you to reject the null hypothesis. 
B) The sample mean should be very different from 80 and should lead you to fail to reject the null hypothesis. 
C) The sample mean should be close to 80 and should lead you to reject the null hypothesis. 
D) The sample mean should be close 80 and should lead you to fail to reject the null hypothesis.

Question 19

What is the consequence of a Type I 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 20

Although the size of the sample can influence the outcome of a hypothesis test, it has little or no influence on measures of effect size.

Accepted Answer

A) True 
 B)False

Increasing the alpha level (for example from α = .01 to α = .05) _____.

In general, the null hypothesis states that the treatment has no effect on the population mean.

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.

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

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?

The power of a hypothesis test is the probability that the sample mean will be in the critical region if the treatment has an effect.

A Type I error occurs when a treatment actually does have an effect on the scores but the effect was not large enough to reject the null hypothesis.

If a hypothesis test is found to have power = 0.70, then what is the probability that the test will result in a Type II error?

Which of the following is an accurate definition of a Type II error?

Which of the following is an accurate definition of a Type I error?

A researcher is conducting an experiment to evaluate a treatment that is expected to increase the scores for individuals in a population.If the researcher uses a one-tailed test with $\alpha$ = .01, then which of the following correctly identifies the critical region?

Even if a treatment has no effect it is still possible to obtain an extreme sample mean that is very different from the population mean.What outcome is likely if this happens?

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, then what is the correct statistical decision?

Which of the following will increase the power of a statistical test?

In a research report, the notation p < .05 indicates that the probability of a Type I error is less than .05.

The critical region for a hypothesis test consists of sample outcomes that are very unlikely to occur if the null hypothesis is true.

In a hypothesis test, the value obtained for the z-score is independent of the sample size.

A sample of n = 25 individuals is selected from a population with µ = 80 and a treatment is administered to the sample.What is expected if the treatment has no effect?

What is the consequence of a Type I error?

Although the size of the sample can influence the outcome of a hypothesis test, it has little or no influence on measures of effect size.

Introduction to Statistics

Frequency Distributions

Central Tendency

Variability

Z-Scores

Probability

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 Anova

Two-Factor Analysis of Variance

Correlation

Introduction to Regression

Chi-Square Tests

The Binomial Test

Choosing the Right Statistics

Filters

Exam 8: Introduction to Hypothesis Testing

Increasing the alpha level (for example from α = .01 to α = .05) _____.

In general, the null hypothesis states that the treatment has no effect on the population mean.

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.

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

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?

The power of a hypothesis test is the probability that the sample mean will be in the critical region if the treatment has an effect.

A Type I error occurs when a treatment actually does have an effect on the scores but the effect was not large enough to reject the null hypothesis.

If a hypothesis test is found to have power = 0.70, then what is the probability that the test will result in a Type II error?

Which of the following is an accurate definition of a Type II error?

Which of the following is an accurate definition of a Type I error?

A researcher is conducting an experiment to evaluate a treatment that is expected to increase the scores for individuals in a population.If the researcher uses a one-tailed test with α\alphaα = .01, then which of the following correctly identifies the critical region?

Even if a treatment has no effect it is still possible to obtain an extreme sample mean that is very different from the population mean.What outcome is likely if this happens?

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, then what is the correct statistical decision?

Which of the following will increase the power of a statistical test?

In a research report, the notation p < .05 indicates that the probability of a Type I error is less than .05.

The critical region for a hypothesis test consists of sample outcomes that are very unlikely to occur if the null hypothesis is true.

In a hypothesis test, the value obtained for the z-score is independent of the sample size.

A sample of n = 25 individuals is selected from a population with µ = 80 and a treatment is administered to the sample.What is expected if the treatment has no effect?

What is the consequence of a Type I error?

Although the size of the sample can influence the outcome of a hypothesis test, it has little or no influence on measures of effect size.

Introduction to Statistics

Frequency Distributions

Central Tendency

Variability

Z-Scores

Probability

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 Anova

Two-Factor Analysis of Variance

Correlation

Introduction to Regression

Chi-Square Tests

The Binomial Test

Choosing the Right Statistics

Filters

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

A researcher is conducting an experiment to evaluate a treatment that is expected to increase the scores for individuals in a population.If the researcher uses a one-tailed test with $\alpha$ = .01, then which of the following correctly identifies the critical region?