Question 1

If our level of significance is .05, but our statistical test produces a probability of .07, we have confirmed the null hypothesis.

Accepted Answer

A) True 
 B)False  False

Question 2

If the null hypothesis is true:

Accepted Answer

A) The hypothesized relationship really exists. 
B) The results are statistically significant. 
C) The relationship found in our study data between the hypothesized variables can be attributed to sampling error. 
D) All of these. 
A) The hypothesized relationship really exists. 
B) The results are statistically significant. 
C) The relationship found in our study data between the hypothesized variables can be attributed to sampling error. 
D) All of these. C

Question 3

When testing a nondirectional hypothesis, we use a two-tailed test of significance.

Accepted Answer

A) True 
 B)False  True

Question 4

The critical region is that area of the theoretical sampling distribution where our sample statistic needs to fall in order to be deemed statistically significant.

Accepted Answer

A) True 
 B)False

Question 5

The probability that we are willing to risk being wrong in rejecting the null hypothesis is:

Accepted Answer

A) Located in the smaller portion of the theoretical sampling distribution after the cutoff point. 
B) Called the level of significance. 
C) Called the alpha level. 
D) All of these. 
A) Located in the smaller portion of the theoretical sampling distribution after the cutoff point. 
B) Called the level of significance. 
C) Called the alpha level. 
D) All of these.

Question 6

A two-tailed test of significance splits the critical region at both ends of the theoretical sampling distribution.

Accepted Answer

A) True 
 B)False

Question 7

The terms level of significance, alpha level, and critical region each refer to different things; they do not refer to the same thing.

Accepted Answer

A) True 
 B)False

Question 8

A finding that is statistically significant means that:

Accepted Answer

A) Chance is NOT a plausible explanation for our finding. 
B) Our research hypothesis is true. 
C) Flaws in our research design become less relevant. 
D) All of these. 
A) Chance is NOT a plausible explanation for our finding. 
B) Our research hypothesis is true. 
C) Flaws in our research design become less relevant. 
D) All of these.

Question 9

Rejecting the null hypothesis means that our research hypothesis is true, regardless of design issues.

Accepted Answer

A) True 
 B)False

Question 10

If we use a one-tailed test of significance, but get findings that would be significant in the opposite tail, we can reject the null hypothesis and conclude that the results have confirmed the opposite of what we predicted.

Accepted Answer

A) True 
 B)False

Question 11

Which of the following statements is true about theoretical sampling distributions?

Accepted Answer

A) They are based on the assumption that the null hypothesis is true. 
B) They are based on the assumption that the null hypothesis is false. 
C) They are based on the assumption that a study's findings can be attributed to sampling error. 
D) They are based on the assumption that the null hypothesis is true AND that therefore the findings can be attributed to sampling error. 
A) They are based on the assumption that the null hypothesis is true. 
B) They are based on the assumption that the null hypothesis is false. 
C) They are based on the assumption that a study's findings can be attributed to sampling error. 
D) They are based on the assumption that the null hypothesis is true AND that therefore the findings can be attributed to sampling error.

Question 12

When we get findings that warrant rejecting the null hypothesis, we should:

Accepted Answer

A) Remember that design issues might still be alternative explanations for our findings. 
B) Rule out design issues as alternative explanations for our findings. 
C) Conclude that there is no chance whatsoever that our findings could be due to sampling error. 
D) None of these. 
A) Remember that design issues might still be alternative explanations for our findings. 
B) Rule out design issues as alternative explanations for our findings. 
C) Conclude that there is no chance whatsoever that our findings could be due to sampling error. 
D) None of these.

Question 13

The theoretical sampling distribution shows the likelihood of getting a particular finding just due to sampling error.

Accepted Answer

A) True 
 B)False

Question 14

An administrator working in a child guidance center tests the hypothesis that family income will be related to number of treatment sessions attended.Her sample size is large, and her level of significance is .05.How should her critical region appear in her theoretical sampling distribution?

Accepted Answer

A) It should be split between the right and left tails, with .05 appearing in each tail. 
B) It should be split between the right and left tails, with .025 appearing in each tail. 
C) It should appear in the tail signifying a positive relationship, with .05 in that tail. 
D) It should appear in the tail signifying a negative relationship, with .05 in that tail. 
A) It should be split between the right and left tails, with .05 appearing in each tail. 
B) It should be split between the right and left tails, with .025 appearing in each tail. 
C) It should appear in the tail signifying a positive relationship, with .05 in that tail. 
D) It should appear in the tail signifying a negative relationship, with .05 in that tail.

Question 15

When we are testing directional hypotheses, we should:

Accepted Answer

A) Never use a two-tailed test. 
B) Always use a two-tailed test. 
C) Use a two-tailed test if we want to be able to reject the null hypothesis in case our findings are in the opposite direction from the one predicted in our hypothesis. 
D) None of these. 
A) Never use a two-tailed test. 
B) Always use a two-tailed test. 
C) Use a two-tailed test if we want to be able to reject the null hypothesis in case our findings are in the opposite direction from the one predicted in our hypothesis. 
D) None of these.

Question 16

If our findings yield a probability level that falls short of our critical region and therefore is NOT statistically significant, we should:

Accepted Answer

A) Conclude that the null hypothesis has been confirmed. 
B) Fail to reject the null hypothesis. 
C) Conclude that there really is no relationship between our hypothesized variables in the population. 
D) All of these. 
A) Conclude that the null hypothesis has been confirmed. 
B) Fail to reject the null hypothesis. 
C) Conclude that there really is no relationship between our hypothesized variables in the population. 
D) All of these.

Question 17

The cutoff point that separates the critical region probability from the rest of the area of the theoretical sampling distribution can be called the:

Accepted Answer

A) Level of significance. 
B) Rejection level. 
C) Alpha level. 
D) All of these. 
A) Level of significance. 
B) Rejection level. 
C) Alpha level. 
D) All of these.

Question 18

When testing a directional hypothesis, we always must use a one-tailed test of significance; there are no exceptions to this rule.

Accepted Answer

A) True 
 B)False

Question 19

Even if there is some difference in treatment outcome between two groups in our sample, the null hypothesis postulates that the difference can be attributed to sampling error.

Accepted Answer

A) True 
 B)False

Question 20

Which of the following statements is true about one-tailed tests of significance?

Accepted Answer

A) The critical region is at both ends of the theoretical sampling distribution. 
B) They increase the chances of reaching the critical region if the results are in the predicted direction 
C) They are used mainly with very large samples. 
D) They require greater between-group differences in order to reach the critical region. 
A) The critical region is at both ends of the theoretical sampling distribution. 
B) They increase the chances of reaching the critical region if the results are in the predicted direction 
C) They are used mainly with very large samples. 
D) They require greater between-group differences in order to reach the critical region.

If our level of significance is .05, but our statistical test produces a probability of .07, we have confirmed the null hypothesis.

If the null hypothesis is true:

When testing a nondirectional hypothesis, we use a two-tailed test of significance.

The critical region is that area of the theoretical sampling distribution where our sample statistic needs to fall in order to be deemed statistically significant.

The probability that we are willing to risk being wrong in rejecting the null hypothesis is:

A two-tailed test of significance splits the critical region at both ends of the theoretical sampling distribution.

The terms level of significance, alpha level, and critical region each refer to different things; they do not refer to the same thing.

A finding that is statistically significant means that:

Rejecting the null hypothesis means that our research hypothesis is true, regardless of design issues.

If we use a one-tailed test of significance, but get findings that would be significant in the opposite tail, we can reject the null hypothesis and conclude that the results have confirmed the opposite of what we predicted.

Which of the following statements is true about theoretical sampling distributions?

When we get findings that warrant rejecting the null hypothesis, we should:

The theoretical sampling distribution shows the likelihood of getting a particular finding just due to sampling error.

An administrator working in a child guidance center tests the hypothesis that family income will be related to number of treatment sessions attended.Her sample size is large, and her level of significance is .05.How should her critical region appear in her theoretical sampling distribution?

When we are testing directional hypotheses, we should:

If our findings yield a probability level that falls short of our critical region and therefore is NOT statistically significant, we should:

The cutoff point that separates the critical region probability from the rest of the area of the theoretical sampling distribution can be called the:

When testing a directional hypothesis, we always must use a one-tailed test of significance; there are no exceptions to this rule.

Even if there is some difference in treatment outcome between two groups in our sample, the null hypothesis postulates that the difference can be attributed to sampling error.

Which of the following statements is true about one-tailed tests of significance?

Why Study Statistics

Use of Statistics in Evidence-Based Practice

Review of Key Research Methodology Concepts and Terms

Frequency Distributions

Graphs and Charts

Measures of Central Tendency

Measures of Dispersion

Types of Distributions

Z-Scores, Percentiles and Effect Size

Probability and Sampling Distributions

Type I and Type Ii Errors

Interpreting the Strength and Importance of Relationships

The T-Test

Analysis of Variance

Cross Tabulation and Chi-Square

Correlation

Regression Analysis

Applications to Single-System Evaluation Designs

Filters

Exam 11: Hypothesis Testing and Statistical Significance

If our level of significance is .05, but our statistical test produces a probability of .07, we have confirmed the null hypothesis.

If the null hypothesis is true:

When testing a nondirectional hypothesis, we use a two-tailed test of significance.

The critical region is that area of the theoretical sampling distribution where our sample statistic needs to fall in order to be deemed statistically significant.

The probability that we are willing to risk being wrong in rejecting the null hypothesis is:

A two-tailed test of significance splits the critical region at both ends of the theoretical sampling distribution.

The terms level of significance, alpha level, and critical region each refer to different things; they do not refer to the same thing.

A finding that is statistically significant means that:

Rejecting the null hypothesis means that our research hypothesis is true, regardless of design issues.

If we use a one-tailed test of significance, but get findings that would be significant in the opposite tail, we can reject the null hypothesis and conclude that the results have confirmed the opposite of what we predicted.

Which of the following statements is true about theoretical sampling distributions?

When we get findings that warrant rejecting the null hypothesis, we should:

The theoretical sampling distribution shows the likelihood of getting a particular finding just due to sampling error.

An administrator working in a child guidance center tests the hypothesis that family income will be related to number of treatment sessions attended.Her sample size is large, and her level of significance is .05.How should her critical region appear in her theoretical sampling distribution?

When we are testing directional hypotheses, we should:

If our findings yield a probability level that falls short of our critical region and therefore is NOT statistically significant, we should:

The cutoff point that separates the critical region probability from the rest of the area of the theoretical sampling distribution can be called the:

When testing a directional hypothesis, we always must use a one-tailed test of significance; there are no exceptions to this rule.

Even if there is some difference in treatment outcome between two groups in our sample, the null hypothesis postulates that the difference can be attributed to sampling error.

Which of the following statements is true about one-tailed tests of significance?

Why Study Statistics

Use of Statistics in Evidence-Based Practice

Review of Key Research Methodology Concepts and Terms

Frequency Distributions

Graphs and Charts

Measures of Central Tendency

Measures of Dispersion

Types of Distributions

Z-Scores, Percentiles and Effect Size

Probability and Sampling Distributions

Type I and Type Ii Errors

Interpreting the Strength and Importance of Relationships

The T-Test

Analysis of Variance

Cross Tabulation and Chi-Square

Correlation

Regression Analysis

Applications to Single-System Evaluation Designs

Filters