Question 1

Another name for sampling error is

Accepted Answer

A)  variability due to chance. 
B)  error variance. 
C)  constancy. 
D)  both a and b 
A)  variability due to chance. 
B)  error variance. 
C)  constancy. 
D)  both a and b D

Question 2

The central feature of all hypothesis testing procedures is

Accepted Answer

A)  the sample mean. 
B)  a sampling distribution. 
C)  a range of outcomes. 
D)  the type of experiment we run. 
A)  the sample mean. 
B)  a sampling distribution. 
C)  a range of outcomes. 
D)  the type of experiment we run. B

Question 3

Give an example of a hypothesis that would be appropriate for testing with a one-tailed test.

Accepted Answer

Examples include: 
Males are more physically aggressive than females. 
Freshman are more homesick the first week of school than sophomores.

Question 4

The basic reason for running an experiment is usually to

Accepted Answer

A)  reject the null hypothesis. 
B)  reject the experimental hypothesis. 
C)  reject the research hypothesis. 
D)  find a non-significant difference. 
A)  reject the null hypothesis. 
B)  reject the experimental hypothesis. 
C)  reject the research hypothesis. 
D)  find a non-significant difference.

Question 5

Type I error is rejecting the null hypothesis when it is true.

Accepted Answer

A) True 
 B)False

Question 6

Sampling distributions help us test hypotheses about means by

Accepted Answer

A)  telling us exactly what the population mean is. 
B)  telling us how variable the population is. 
C)  telling us what kinds of means to expect if the null hypothesis is true. 
D)  telling us what kinds of means to expect if the null hypothesis is false. 
A)  telling us exactly what the population mean is. 
B)  telling us how variable the population is. 
C)  telling us what kinds of means to expect if the null hypothesis is true. 
D)  telling us what kinds of means to expect if the null hypothesis is false.

Question 7

A two-tailed test is _______ powerful than a one-tailed test if we are sure the difference is in the direction that we would have predicted.

Accepted Answer

A)  more 
B)  less 
C)  equally 
D)  We cannot tell. 
A)  more 
B)  less 
C)  equally 
D)  We cannot tell.

Question 8

Type II error is retaining the null hypothesis when it is true.

Accepted Answer

A) True 
 B)False

Question 9

If the data are reasonably consistent with the null hypothesis, we are likely to

Accepted Answer

A)  accept the alternative hypothesis. 
B)  reject the null hypothesis. 
C)  retain the null hypothesis. 
D)  accept the null hypothesis. 
A)  accept the alternative hypothesis. 
B)  reject the null hypothesis. 
C)  retain the null hypothesis. 
D)  accept the null hypothesis.

Question 10

Which of the following is a statement of H 1?

Accepted Answer

A)  H 1 : m > 0 
B)  H 1 : m 
C)  H 1 : m  ≠ 0 
D)  all of the above 
A)  H 1 : m > 0 
B)  H 1 : m 
C)  H 1 : m  ≠ 0 
D)  all of the above

Question 11

When testing a hypothesis, we normally retain the null hypothesis when the test statistic is smaller than the critical value.

Accepted Answer

A) True 
 B)False

Question 12

Power is the probability of making a Type II error.

Accepted Answer

A) True 
 B)False

Question 13

Rejecting a true null hypothesis is known as

Accepted Answer

A)  Type II Error 
B)  Type I Error 
C)  alpha ( a ) 
D)  both b and c 
A)  Type II Error 
B)  Type I Error 
C)  alpha ( a ) 
D)  both b and c

Question 14

To reject a null hypothesis for the finger tapping example in the text, we would

Accepted Answer

A)  calculate the probability of that result if the null hypothesis were false. 
B)  calculate the probability of that result if the null hypothesis were true. 
C)  compare the probabilities of that result if the null hypothesis were true and if it were false. 
D)  reject the null hypothesis unless that subject closely resembled normal subjects. 
A)  calculate the probability of that result if the null hypothesis were false. 
B)  calculate the probability of that result if the null hypothesis were true. 
C)  compare the probabilities of that result if the null hypothesis were true and if it were false. 
D)  reject the null hypothesis unless that subject closely resembled normal subjects.

Question 15

After running a t-test on the mean numbers of jelly beans that men and women eat over the course of the year, I conclude that men eat significantly more jelly beans than women. If men and women actually eat the same number of jelly beans, my conclusion is

Accepted Answer

A)  a valid conclusion 
B)  a Type I error 
C)  a Type II error 
D)  an example of power 
A)  a valid conclusion 
B)  a Type I error 
C)  a Type II error 
D)  an example of power

Question 16

The value of the test statistic that would lead us to reject the null hypothesis is called

Accepted Answer

A)  the critical value. 
B)  the test value. 
C)  the rejection value. 
D)  the acceptance value. 
A)  the critical value. 
B)  the test value. 
C)  the rejection value. 
D)  the acceptance value.

Question 17

If we were to repeat an experiment a large number of times and calculate a statistic such as the mean for each experiment, the distribution of these statistics would be called

Accepted Answer

A)  the distributional distribution 
B)  the error distribution. 
C)  the sampling distribution. 
D)  the test outcome. 
A)  the distributional distribution 
B)  the error distribution. 
C)  the sampling distribution. 
D)  the test outcome.

Question 18

The basic idea behind hypothesis testing

Accepted Answer

A)  depends on the kind of test you want to run. 
B)  has little to do with whatever data you collect. 
C)  is largely the same across a wide variety of procedures. 
D)  is important only if you want to compare two populations. 
A)  depends on the kind of test you want to run. 
B)  has little to do with whatever data you collect. 
C)  is largely the same across a wide variety of procedures. 
D)  is important only if you want to compare two populations.

Question 19

In hypothesis testing our job would be much easier if

Accepted Answer

A)  sample statistics accurately reflected population parameters. 
B)  subjects didn't vary so much from one another. 
C)  we knew the population values. 
D)  all of the above 
A)  sample statistics accurately reflected population parameters. 
B)  subjects didn't vary so much from one another. 
C)  we knew the population values. 
D)  all of the above

Question 20

When we are willing to reject the null hypothesis for any extreme outcome, we are making a

Accepted Answer

A)  two-tailed test. 
B)  one-tailed test. 
C)  singular test. 
D)  omnibus test. 
A)  two-tailed test. 
B)  one-tailed test. 
C)  singular test. 
D)  omnibus test.

Exam 8: Sampling Distributions and Hypothesis Testing

Another name for sampling error is

The central feature of all hypothesis testing procedures is

Give an example of a hypothesis that would be appropriate for testing with a one-tailed test.

The basic reason for running an experiment is usually to

Type I error is rejecting the null hypothesis when it is true.

Sampling distributions help us test hypotheses about means by

A two-tailed test is _______ powerful than a one-tailed test if we are sure the difference is in the direction that we would have predicted.

Type II error is retaining the null hypothesis when it is true.

If the data are reasonably consistent with the null hypothesis, we are likely to

Which of the following is a statement of H 1?

When testing a hypothesis, we normally retain the null hypothesis when the test statistic is smaller than the critical value.

Power is the probability of making a Type II error.

Rejecting a true null hypothesis is known as

To reject a null hypothesis for the finger tapping example in the text, we would

After running a t-test on the mean numbers of jelly beans that men and women eat over the course of the year, I conclude that men eat significantly more jelly beans than women. If men and women actually eat the same number of jelly beans, my conclusion is

The value of the test statistic that would lead us to reject the null hypothesis is called

If we were to repeat an experiment a large number of times and calculate a statistic such as the mean for each experiment, the distribution of these statistics would be called

The basic idea behind hypothesis testing

In hypothesis testing our job would be much easier if

When we are willing to reject the null hypothesis for any extreme outcome, we are making a

Introduction

Basic Concepts

Displaying Data

Measures of Central Tendency

Measures of Variability

The Normal Distribution

Basic Concepts of Probability

Correlation

Regression

Multiple Regression

Hypothesis Tests Applied to Means: One Sample

Hypothesis Tests Applied to Means: Two Related Samples

Hypothesis Tests Applied to Means: Two Independent Samples

Power

One-Way Analysis of Variance

Factorial Analysis of Variance

Repeated-Measures Analysis of Variance

Chi-Square

Nonparametric and Resampling Statistical Tests

Meta-Analysis

Filters

Which of the following is a statement of H ₁?