Question 1

A lower p-value in one study means that the finding is more important than the finding of another study with a higher p -value.

Accepted Answer

A) True 
 B)False  False

Question 2

The most appropriate significance level in evidence-based practice research:

Accepted Answer

A) Should always be .05. 
B) Should always be .10. 
C) Is determined by mathematical theory. 
D) Can vary, depending upon the sample size and judgments about the relative seriousness of Type I and Type II errors. 
A) Should always be .05. 
B) Should always be .10. 
C) Is determined by mathematical theory. 
D) Can vary, depending upon the sample size and judgments about the relative seriousness of Type I and Type II errors. D

Question 3

The Type II error probability is the proportion of the predicted sampling distribution that falls within the significant tail of the null hypothesis sampling distribution.

Accepted Answer

A) True 
 B)False  False

Question 4

Which of the following statements is true about Type I and Type II errors?

Accepted Answer

A) Type I errors are always more serious. 
B) Type II errors are always more serious. 
C) Type I and Type II errors are always equally serious. 
D) Which error is more serious will vary from study to study depending on the value judgments that we make. 
A) Type I errors are always more serious. 
B) Type II errors are always more serious. 
C) Type I and Type II errors are always equally serious. 
D) Which error is more serious will vary from study to study depending on the value judgments that we make.

Question 5

In evidence-based practice research, Type I errors are always more serious than Type II errors.

Accepted Answer

A) True 
 B)False

Question 6

We commit a Type II error when we:

Accepted Answer

A) Reject a true null hypothesis. 
B) Fail to reject a false null hypothesis. 
C) Fail to reject a false research hypothesis. 
D) Reject a false null hypothesis 
A) Reject a true null hypothesis. 
B) Fail to reject a false null hypothesis. 
C) Fail to reject a false research hypothesis. 
D) Reject a false null hypothesis

Question 7

If the statewide re-arrest rate for drinking and driving is 40% and we predict that recipients of a new intervention to prevent recidivism will have a 10% recidivism rate, then:

Accepted Answer

A) the mean of the theoretical sampling distribution of the null hypothesis will be 40%. 
B) the mean of the theoretical sampling distribution of the research hypothesis will be 10%. 
C) the mean of the theoretical sampling distribution of the research hypothesis will be 30%. 
D) the mean of the theoretical sampling distribution of the null hypothesis will be 30%. 
A) the mean of the theoretical sampling distribution of the null hypothesis will be 40%. 
B) the mean of the theoretical sampling distribution of the research hypothesis will be 10%. 
C) the mean of the theoretical sampling distribution of the research hypothesis will be 30%. 
D) the mean of the theoretical sampling distribution of the null hypothesis will be 30%.

Question 8

In evidence-based practice research, Type II errors are always more serious than Type I errors.

Accepted Answer

A) True 
 B)False

Question 9

Statistical conclusion validity:

Accepted Answer

A) Is based on the quality of data collection methods. 
B) Is based on the strength of the logic of the research design. 
C) Can be found in a study that lacks internal validity. 
D) Requires that the relationship be strong. 
A) Is based on the quality of data collection methods. 
B) Is based on the strength of the logic of the research design. 
C) Can be found in a study that lacks internal validity. 
D) Requires that the relationship be strong.

Question 10

A Type I error occurs whenever we reject a true null hypothesis.

Accepted Answer

A) True 
 B)False

Question 11

Although the null hypothesis may be implausible, it is never impossible.

Accepted Answer

A) True 
 B)False

Question 12

We commit a Type I error when we:

Accepted Answer

A) Reject a true null hypothesis. 
B) Fail to reject a false null hypothesis. 
C) Reject a true research hypothesis. 
D) Fail to reject a false research hypothesis. 
A) Reject a true null hypothesis. 
B) Fail to reject a false null hypothesis. 
C) Reject a true research hypothesis. 
D) Fail to reject a false research hypothesis.

Question 13

Our risk of a Type II error increases the most when:

Accepted Answer

A) Our sample size decreases, and we select a lower significance level (such as .01). 
B) Our sample size increases, and we select a higher significance level (such as .10). 
C) Our sample size decreases, and we select a higher significance level (such as .10). 
D) Our sample size increases, and we select a lower significance level (such as .01). 
A) Our sample size decreases, and we select a lower significance level (such as .01). 
B) Our sample size increases, and we select a higher significance level (such as .10). 
C) Our sample size decreases, and we select a higher significance level (such as .10). 
D) Our sample size increases, and we select a lower significance level (such as .01).

Question 14

Which of the following statements is/are correct about p-values and significance levels?

Accepted Answer

A) If the p-value is .04, and the significance level is .05, then the result is statistically significant. 
B) If the p-value is .05, and the significance level is .04, then the result is statistically significant. 
C) If the p-value is .051, and the significance level is .05, then the result is statistically significant. 
D) All of these. 
A) If the p-value is .04, and the significance level is .05, then the result is statistically significant. 
B) If the p-value is .05, and the significance level is .04, then the result is statistically significant. 
C) If the p-value is .051, and the significance level is .05, then the result is statistically significant. 
D) All of these.

Question 15

When our results are statistically significant, we refuse to reject the null hypothesis.

Accepted Answer

A) True 
 B)False

Question 16

An experiment with a small sample is conducted to test the effectiveness of a promising new intervention for treating substance abuse.The experimental group's outcome is better than the control group's outcome, but the results are not statistically significant.The implication of this finding for evidence-based practice is:

Accepted Answer

A) The new intervention was ineffective. 
B) The new intervention was effective, but not as effective as predicted. 
C) It is conceivable that the new intervention is effective, although we cannot rule out sampling error as the explanation for the research finding.Additional testing of this intervention with a larger sample size would be in order. 
D) None of these. 
A) The new intervention was ineffective. 
B) The new intervention was effective, but not as effective as predicted. 
C) It is conceivable that the new intervention is effective, although we cannot rule out sampling error as the explanation for the research finding.Additional testing of this intervention with a larger sample size would be in order. 
D) None of these.

Question 17

A Type II error occurs when we fail to reject a false null hypothesis.

Accepted Answer

A) True 
 B)False

Question 18

We risk a Type I error when we;

Accepted Answer

A) Reject the null hypothesis. 
B) Fail to reject the null hypothesis. 
C) Obtain results that are NOT statistically significant. 
D) Reject a true research hypothesis. 
A) Reject the null hypothesis. 
B) Fail to reject the null hypothesis. 
C) Obtain results that are NOT statistically significant. 
D) Reject a true research hypothesis.

Question 19

We are least susceptible to committing Type II errors when our sample is small.

Accepted Answer

A) True 
 B)False

Question 20

Which of the following statements is true about risking a Type II error?

Accepted Answer

A) We risk it when we reject the null hypothesis. 
B) We risk it when we fail to reject the null hypothesis. 
C) The same decision as to whether or not to reject a null hypothesis can risk a Type I and Type II error simultaneously. 
D) None of these. 
A) We risk it when we reject the null hypothesis. 
B) We risk it when we fail to reject the null hypothesis. 
C) The same decision as to whether or not to reject a null hypothesis can risk a Type I and Type II error simultaneously. 
D) None of these.

A lower p-value in one study means that the finding is more important than the finding of another study with a higher p -value.

The most appropriate significance level in evidence-based practice research:

The Type II error probability is the proportion of the predicted sampling distribution that falls within the significant tail of the null hypothesis sampling distribution.

Which of the following statements is true about Type I and Type II errors?

In evidence-based practice research, Type I errors are always more serious than Type II errors.

We commit a Type II error when we:

If the statewide re-arrest rate for drinking and driving is 40% and we predict that recipients of a new intervention to prevent recidivism will have a 10% recidivism rate, then:

In evidence-based practice research, Type II errors are always more serious than Type I errors.

Statistical conclusion validity:

A Type I error occurs whenever we reject a true null hypothesis.

Although the null hypothesis may be implausible, it is never impossible.

We commit a Type I error when we:

Our risk of a Type II error increases the most when:

Which of the following statements is/are correct about p-values and significance levels?

When our results are statistically significant, we refuse to reject the null hypothesis.

A Type II error occurs when we fail to reject a false null hypothesis.

We risk a Type I error when we;

We are least susceptible to committing Type II errors when our sample is small.

Which of the following statements is true about risking a Type II error?

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

Hypothesis Testing and Statistical Significance

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 12: Type I and Type Ii Errors

A lower p-value in one study means that the finding is more important than the finding of another study with a higher p -value.

The most appropriate significance level in evidence-based practice research:

The Type II error probability is the proportion of the predicted sampling distribution that falls within the significant tail of the null hypothesis sampling distribution.

Which of the following statements is true about Type I and Type II errors?

In evidence-based practice research, Type I errors are always more serious than Type II errors.

We commit a Type II error when we:

If the statewide re-arrest rate for drinking and driving is 40% and we predict that recipients of a new intervention to prevent recidivism will have a 10% recidivism rate, then:

In evidence-based practice research, Type II errors are always more serious than Type I errors.

Statistical conclusion validity:

A Type I error occurs whenever we reject a true null hypothesis.

Although the null hypothesis may be implausible, it is never impossible.

We commit a Type I error when we:

Our risk of a Type II error increases the most when:

Which of the following statements is/are correct about p-values and significance levels?

When our results are statistically significant, we refuse to reject the null hypothesis.

A Type II error occurs when we fail to reject a false null hypothesis.

We risk a Type I error when we;

We are least susceptible to committing Type II errors when our sample is small.

Which of the following statements is true about risking a Type II error?

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

Hypothesis Testing and Statistical Significance

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