Deck 4: Factorial Analysis of Variance

Question 1

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.

Answer 1

True

Question 2

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

Answer 2

True

Question 3

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

Answer 3

True

Question 4

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

Question 5

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

Question 6

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

Question 7

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.

Question 8

The test statistic for ANOVA is partial eta squared.

Question 9

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

Question 10

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

Question 11

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.

Question 12

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.

Question 13

Post hoc tests are also known as multiple comparisons.

Question 14

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

Question 15

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

Question 16

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

Question 17

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

Question 18

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

Question 19

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

Question 20

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

Question 21

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

Question 22

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.

Question 23

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.

Question 24

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

Question 25

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

Question 26

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

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 27

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

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.

Question 28

In two-way analysis of variance:

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 29

Main effects in the two-way ANOVA:

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 30

Interaction between factors in the two-way ANOVA:

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.