Question 1

Interpreting the strength and practical implications of effect sizes based on correlation coefficients is:

Accepted Answer

A) The same as interpreting percentage scores of exams. 
B) The same as interpreting correlation coefficients in studies of instrument reliability. 
C) Less meaningful than just asking whether the correlation is statistically significant. 
D) None of these. 
A) The same as interpreting percentage scores of exams. 
B) The same as interpreting correlation coefficients in studies of instrument reliability. 
C) Less meaningful than just asking whether the correlation is statistically significant. 
D) None of these.

Question 2

Which of the following is true about correlation statistics?

Accepted Answer

A) A negative correlation of -.50 is weaker than a positive correlation +.30. 
B) A positive correlation of +.50 is stronger than a negative correlation -.50. 
C) A negative correlation of -.30 is stronger than a positive correlation of +.25. 
D) A negative correlation of -.30 is stronger than a positive correlation +.30. 
A) A negative correlation of -.50 is weaker than a positive correlation +.30. 
B) A positive correlation of +.50 is stronger than a negative correlation -.50. 
C) A negative correlation of -.30 is stronger than a positive correlation of +.25. 
D) A negative correlation of -.30 is stronger than a positive correlation +.30.

Question 3

The statistical power of a study is its probability of correctly rejecting a null hypothesis that is false.

Accepted Answer

A) True 
 B)False

Question 4

We would increase statistical power if we:

Accepted Answer

A) Increase the sample size. 
B) Assume a smaller effect size in the population. 
C) Decrease the significance level from .05 to .01. 
D) Decrease the sample size 
A) Increase the sample size. 
B) Assume a smaller effect size in the population. 
C) Decrease the significance level from .05 to .01. 
D) Decrease the sample size

Question 5

Which of the following is true about correlation statistics?

Accepted Answer

A) A negative correlation is always undesirable. 
B) A strong positive correlation is always desirable. 
C) A weak correlation in one study might be more desirable than a strong correlation in another study if the two studies differ with regard to what variables are being correlated. 
D) A strong correlation is always more desirable than a weak correlation, 
A) A negative correlation is always undesirable. 
B) A strong positive correlation is always desirable. 
C) A weak correlation in one study might be more desirable than a strong correlation in another study if the two studies differ with regard to what variables are being correlated. 
D) A strong correlation is always more desirable than a weak correlation,

Question 6

Substantive significance refers to how meaningful a finding is to clients, significant others, society or practitioners concerned about a problem.

Accepted Answer

A) True 
 B)False

Question 7

Which of the following is true about correlation statistics?

Accepted Answer

A) For two variables to be correlated, there can be no exceptions to the pattern in which increases in one variable is accompanied by increases in the other variable. 
B) Two variables can be correlated if increases in one variable are accompanied by decreases in the other variable with most cases, but not necessarily with all cases. 
C) Two variables cannot be correlated if one decreases while the other increases. 
D) When both variables are at the ratio level of measurement, a nonparametric correlation coefficient must be used. 
A) For two variables to be correlated, there can be no exceptions to the pattern in which increases in one variable is accompanied by increases in the other variable. 
B) Two variables can be correlated if increases in one variable are accompanied by decreases in the other variable with most cases, but not necessarily with all cases. 
C) Two variables cannot be correlated if one decreases while the other increases. 
D) When both variables are at the ratio level of measurement, a nonparametric correlation coefficient must be used.

Interpreting the strength and practical implications of effect sizes based on correlation coefficients is:

Which of the following is true about correlation statistics?

The statistical power of a study is its probability of correctly rejecting a null hypothesis that is false.

We would increase statistical power if we:

Which of the following is true about correlation statistics?

Substantive significance refers to how meaningful a finding is to clients, significant others, society or practitioners concerned about a problem.

Which of the following is true about correlation statistics?

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

Type I and Type Ii Errors

The T-Test

Analysis of Variance

Cross Tabulation and Chi-Square

Correlation

Regression Analysis

Applications to Single-System Evaluation Designs

Filters

Exam 13: Interpreting the Strength and Importance of Relationships

Interpreting the strength and practical implications of effect sizes based on correlation coefficients is:

Which of the following is true about correlation statistics?

The statistical power of a study is its probability of correctly rejecting a null hypothesis that is false.

We would increase statistical power if we:

Which of the following is true about correlation statistics?

Substantive significance refers to how meaningful a finding is to clients, significant others, society or practitioners concerned about a problem.

Which of the following is true about correlation statistics?

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

Type I and Type Ii Errors

The T-Test

Analysis of Variance

Cross Tabulation and Chi-Square

Correlation

Regression Analysis

Applications to Single-System Evaluation Designs

Filters