Question 1

A two-way ANOVA consists of two DVs and one IV.

Accepted Answer

A) True 
 B)False  False

Question 2

When the value of the F ratio in ANOVA is near 1.00, this indicates that:

Accepted Answer

A)  The differences between groups in the factor are roughly the same as would be expected due to chance. 
B)  There is evidence of a treatment effect. 
C)  There is no evidence of a treatment effect. 
D)  Both (a) and (c) are correct. 
A)  The differences between groups in the factor are roughly the same as would be expected due to chance. 
B)  There is evidence of a treatment effect. 
C)  There is no evidence of a treatment effect. 
D)  Both (a) and (c) are correct. D

Question 3

One-way ANOVA studies the effect that one factor has on one DV.

Accepted Answer

A) True 
 B)False  True

Question 4

The simplest of factorial designs is the two-way analysis of variance (ANOVA).

Accepted Answer

A) True 
 B)False

Question 5

Main effects in the two-way ANOVA:

Accepted Answer

A)  Must be reported when there are interaction effects between the independent variables. 
B)  Need not be reported when the interaction effect between the independent variables is statistically significant. 
C)  Indicate the differences produced by either Factor A or Factor B, independent of the other. 
D)  Both (b) and (c) are correct. 
A)  Must be reported when there are interaction effects between the independent variables. 
B)  Need not be reported when the interaction effect between the independent variables is statistically significant. 
C)  Indicate the differences produced by either Factor A or Factor B, independent of the other. 
D)  Both (b) and (c) are correct.

Question 6

Another possible cause or explanation for the differences that occur between groups or treatments in ANOVA is that the differences occur simply due to chance.

Accepted Answer

A) True 
 B)False

Question 7

The null hypothesis for the tests of an interaction effect with a factorial ANOVA states that there is no interaction between Factor A and Factor B.

Accepted Answer

A) True 
 B)False

Question 8

The validity of the results of a factorial ANOVA is dependent upon three assumptions, one of them being that the distributions of scores on the DV must have equal variances.

Accepted Answer

A) True 
 B)False

Question 9

The null hypothesis for the main effect states that there is a difference in the scores due to the level of A

Accepted Answer

A) True 
 B)False

Question 10

The F ratio in ANOVA is based on mean differences as opposed to variances.

Accepted Answer

A) True 
 B)False

Question 11

The univariate case of ANOVA is a hypothesis-testing procedure that simultaneously evaluates the significance of mean differences on a DV between two or more treatment conditions or groups.

Accepted Answer

A) True 
 B)False

Question 12

Interaction between factors occurs when the effect of one factor depends on different levels of the other factors.

Accepted Answer

A) True 
 B)False

Question 13

Post hoc tests are also known as multiple comparisons.

Accepted Answer

A) True 
 B)False

Question 14

Eta squared is viewed as a descriptive statistic and is interpreted as a measure of effect size.

Accepted Answer

A) True 
 B)False

Question 15

The test statistic for ANOVA is partial eta squared.

Accepted Answer

A) True 
 B)False

Question 16

The null hypothesis in a one-way ANOVA states that there is no difference among the treatment conditions or groups.

Accepted Answer

A) True 
 B)False

Question 17

In two-way analysis of variance:

Accepted Answer

A)  There are two independent variables and one dependent variable. 
B)  There are two dependent variables and one independent variable. 
C)  The two independent variables must be at the interval/ratio level of measurement. 
D)  Both (b) and (c) are incorrect. 
A)  There are two independent variables and one dependent variable. 
B)  There are two dependent variables and one independent variable. 
C)  The two independent variables must be at the interval/ratio level of measurement. 
D)  Both (b) and (c) are incorrect.

Question 18

The alternative or research hypothesis says that at least one of the group or treatment means is significantly different from the others.

Accepted Answer

A) True 
 B)False

Question 19

What level of measurement is required for the independent variable (factor) and dependent variable in univariate analysis of variance (ANOVA)?

Accepted Answer

A)  The factor has to be at the nominal level of measurement. 
B)  The dependent variable has to be at the interval/ratio level of measurement. 
C)  Both of the above. 
D)  Neither of the above. 
A)  The factor has to be at the nominal level of measurement. 
B)  The dependent variable has to be at the interval/ratio level of measurement. 
C)  Both of the above. 
D)  Neither of the above.

Question 20

Another possible interpretation of the results of a one-way ANOVA is that any expected differences between the conditions or groups represent real differences in the population.

Accepted Answer

A) True 
 B)False

A two-way ANOVA consists of two DVs and one IV.

When the value of the F ratio in ANOVA is near 1.00, this indicates that:

One-way ANOVA studies the effect that one factor has on one DV.

The simplest of factorial designs is the two-way analysis of variance (ANOVA).

Main effects in the two-way ANOVA:

Another possible cause or explanation for the differences that occur between groups or treatments in ANOVA is that the differences occur simply due to chance.

The null hypothesis for the tests of an interaction effect with a factorial ANOVA states that there is no interaction between Factor A and Factor B.

The validity of the results of a factorial ANOVA is dependent upon three assumptions, one of them being that the distributions of scores on the DV must have equal variances.

The null hypothesis for the main effect states that there is a difference in the scores due to the level of A

The F ratio in ANOVA is based on mean differences as opposed to variances.

The univariate case of ANOVA is a hypothesis-testing procedure that simultaneously evaluates the significance of mean differences on a DV between two or more treatment conditions or groups.

Interaction between factors occurs when the effect of one factor depends on different levels of the other factors.

Post hoc tests are also known as multiple comparisons.

Eta squared is viewed as a descriptive statistic and is interpreted as a measure of effect size.

The test statistic for ANOVA is partial eta squared.

The null hypothesis in a one-way ANOVA states that there is no difference among the treatment conditions or groups.

In two-way analysis of variance:

The alternative or research hypothesis says that at least one of the group or treatment means is significantly different from the others.

What level of measurement is required for the independent variable (factor) and dependent variable in univariate analysis of variance (ANOVA)?

Another possible interpretation of the results of a one-way ANOVA is that any expected differences between the conditions or groups represent real differences in the population.

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

A two-way ANOVA consists of two DVs and one IV.

When the value of the F ratio in ANOVA is near 1.00, this indicates that:

One-way ANOVA studies the effect that one factor has on one DV.

The simplest of factorial designs is the two-way analysis of variance (ANOVA).

Main effects in the two-way ANOVA:

Another possible cause or explanation for the differences that occur between groups or treatments in ANOVA is that the differences occur simply due to chance.

The null hypothesis for the tests of an interaction effect with a factorial ANOVA states that there is no interaction between Factor A and Factor B.

The validity of the results of a factorial ANOVA is dependent upon three assumptions, one of them being that the distributions of scores on the DV must have equal variances.

The null hypothesis for the main effect states that there is a difference in the scores due to the level of A

The F ratio in ANOVA is based on mean differences as opposed to variances.

The univariate case of ANOVA is a hypothesis-testing procedure that simultaneously evaluates the significance of mean differences on a DV between two or more treatment conditions or groups.

Interaction between factors occurs when the effect of one factor depends on different levels of the other factors.

Post hoc tests are also known as multiple comparisons.

Eta squared is viewed as a descriptive statistic and is interpreted as a measure of effect size.

The test statistic for ANOVA is partial eta squared.

The null hypothesis in a one-way ANOVA states that there is no difference among the treatment conditions or groups.

In two-way analysis of variance:

The alternative or research hypothesis says that at least one of the group or treatment means is significantly different from the others.

What level of measurement is required for the independent variable (factor) and dependent variable in univariate analysis of variance (ANOVA)?

Another possible interpretation of the results of a one-way ANOVA is that any expected differences between the conditions or groups represent real differences in the population.

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