Question 1

Eta squared is commonly viewed as the proportion of variance in the DV explained by the IVs in the sample.

Accepted Answer

A) True 
 B)False

Question 2

Research designs that include more than one factor are called factorial designs.

Accepted Answer

A) True 
 B)False

Question 3

The two-way ANOVA tests two separate hypotheses simultaneously in one analysis.

Accepted Answer

A) True 
 B)False

Question 4

One possible interpretation of the results of a one-way ANOVA is that there really are differences between the treatment conditions or groups.

Accepted Answer

A) True 
 B)False

Question 5

Interaction between factors in the two-way ANOVA:

Accepted Answer

A)  Occurs when the effect of one factor depends on the different levels of the other factor. 
B)  Occurs when the effect of one factor does not depend on the different level of the other factor. 
C)  Should be reported in addition to the main effects for Factor A and Factor 
D)  Both (a) and (c) are correct. 
A)  Occurs when the effect of one factor depends on the different levels of the other factor. 
B)  Occurs when the effect of one factor does not depend on the different level of the other factor. 
C)  Should be reported in addition to the main effects for Factor A and Factor 
D)  Both (a) and (c) are correct.

Question 6

The purpose of factorial ANOVA is to test the mean differences with respect to some IV.

Accepted Answer

A) True 
 B)False

Question 7

The numerator of the F ratio is referred to as the error variance.

Accepted Answer

A) True 
 B)False

Question 8

Any dependent differences produced by either Factor A or Factor B are called main effects.

Accepted Answer

A) True 
 B)False

Question 9

One of the two possible causes or explanations for the differences that occur between groups or treatments in ANOVA is that the differences are due to treatment effects.

Accepted Answer

A) True 
 B)False

Question 10

The treatment conditions or groups are defined by the various levels of the IV, or factor in ANOVA terminology.

Accepted Answer

A) True 
 B)False

Eta squared is commonly viewed as the proportion of variance in the DV explained by the IVs in the sample.

Research designs that include more than one factor are called factorial designs.

The two-way ANOVA tests two separate hypotheses simultaneously in one analysis.

One possible interpretation of the results of a one-way ANOVA is that there really are differences between the treatment conditions or groups.

Interaction between factors in the two-way ANOVA:

The purpose of factorial ANOVA is to test the mean differences with respect to some IV.

The numerator of the F ratio is referred to as the error variance.

Any dependent differences produced by either Factor A or Factor B are called main effects.

One of the two possible causes or explanations for the differences that occur between groups or treatments in ANOVA is that the differences are due to treatment effects.

The treatment conditions or groups are defined by the various levels of the IV, or factor in ANOVA terminology.

Introduction to Multivariate Statistics

A Guide to Multivariate Techniques

Pre-Analysis Data Screening

Analysis of Covariance

Multivariate Analysis of Variance and Covariance

Multiple Regression

Path Analysis

Factor Analysis

Discriminant Analysis

Logistic Regression

Filters

Exam 4: Factorial Analysis of Variance

Eta squared is commonly viewed as the proportion of variance in the DV explained by the IVs in the sample.

Research designs that include more than one factor are called factorial designs.

The two-way ANOVA tests two separate hypotheses simultaneously in one analysis.

One possible interpretation of the results of a one-way ANOVA is that there really are differences between the treatment conditions or groups.

Interaction between factors in the two-way ANOVA:

The purpose of factorial ANOVA is to test the mean differences with respect to some IV.

The numerator of the F ratio is referred to as the error variance.

Any dependent differences produced by either Factor A or Factor B are called main effects.

One of the two possible causes or explanations for the differences that occur between groups or treatments in ANOVA is that the differences are due to treatment effects.

The treatment conditions or groups are defined by the various levels of the IV, or factor in ANOVA terminology.

Introduction to Multivariate Statistics

A Guide to Multivariate Techniques

Pre-Analysis Data Screening

Analysis of Covariance

Multivariate Analysis of Variance and Covariance

Multiple Regression

Path Analysis

Factor Analysis

Discriminant Analysis

Logistic Regression

Filters