Question 1

Which of the following is not included in the three-step process of evaluating a difference?

Accepted Answer

A)  Evaluate if a statistically significant difference has practical significance 
B)  Use a significance to test to determine if a difference is statistically significant 
C)  If there is no significance, one should not assert that the experimental treatment is superior to the control condition and assess for possible practical implications 
D)  Assume that statistically significant difference always has practical significance 
A)  Evaluate if a statistically significant difference has practical significance 
B)  Use a significance to test to determine if a difference is statistically significant 
C)  If there is no significance, one should not assert that the experimental treatment is superior to the control condition and assess for possible practical implications 
D)  Assume that statistically significant difference always has practical significance D

Question 2

Just because a difference is statistically significant does not mean that it is a large difference.

Accepted Answer

A) True 
 B)False  True

Question 3

all statistically significant differences are inherently large and therefore of practical importance.

Accepted Answer

A) True 
 B)False  False

Question 4

Which of the following is NOT true?

Accepted Answer

A)  Small difference can be statistically significant 
B)  Large difference is always practically significant 
C)  Large difference can be practically significant 
D)  Small difference can be practically significant 
A)  Small difference can be statistically significant 
B)  Large difference is always practically significant 
C)  Large difference can be practically significant 
D)  Small difference can be practically significant

Question 5

the fundamental limitations of significance testing are: (1) It fails to indicate the size of a difference, and (2) it does not assess the practical significance of a difference.

Accepted Answer

A) True 
 B)False

Which of the following is not included in the three-step process of evaluating a difference?

Just because a difference is statistically significant does not mean that it is a large difference.

all statistically significant differences are inherently large and therefore of practical importance.

Which of the following is NOT true?

the fundamental limitations of significance testing are: (1) It fails to indicate the size of a difference, and (2) it does not assess the practical significance of a difference.

The Empirical Approach to Knowledge

Types of Empirical Research

Scales of Measurement

Descriptive, Correlational, and Inferential Statistics

Introduction to Sampling

Variations on Random Sampling

Sample Size

Standard Error of the Mean

Frequencies, Percentages, and Proportions

Shapes of Distributions

The Mean: An Average

Mean, Median, and Mode

Range and Interquartile Range

Standard Deviation

Z-Score

Correlation

Pearson-R

Scattergram

Introduction to Hypothesis Testing

Decisions About the Null Hypothesis

Introduction to the T-Test

Independent Samples T-Test

Dependent Samples T-Test

One Sample T-Test

Reports of the Results of T-Tests

One-Way Anova

Two-Way Anova

Chi-Square Test

Effect Size

Coefficient of Determination

Multiple Correlation

Simple and Multiple Regression

Filters

Exam 29: Limitations of Significance Testing

Which of the following is not included in the three-step process of evaluating a difference?

Just because a difference is statistically significant does not mean that it is a large difference.

all statistically significant differences are inherently large and therefore of practical importance.

Which of the following is NOT true?

the fundamental limitations of significance testing are: (1) It fails to indicate the size of a difference, and (2) it does not assess the practical significance of a difference.

The Empirical Approach to Knowledge

Types of Empirical Research

Scales of Measurement

Descriptive, Correlational, and Inferential Statistics

Introduction to Sampling

Variations on Random Sampling

Sample Size

Standard Error of the Mean

Frequencies, Percentages, and Proportions

Shapes of Distributions

The Mean: An Average

Mean, Median, and Mode

Range and Interquartile Range

Standard Deviation

Z-Score

Correlation

Pearson-R

Scattergram

Introduction to Hypothesis Testing

Decisions About the Null Hypothesis

Introduction to the T-Test

Independent Samples T-Test

Dependent Samples T-Test

One Sample T-Test

Reports of the Results of T-Tests

One-Way Anova

Two-Way Anova

Chi-Square Test

Effect Size

Coefficient of Determination

Multiple Correlation

Simple and Multiple Regression

Filters