Factorial Analysis of Variance in Statistics MCQs
Factorial Analysis of Variance in Statistics MCQs
Answer these Factorial Analysis of Variance in Statistics MCQs and see how sharp is your knowledge of Factorial Analysis of Variance in Statistics.
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1: When an experiment design has two factors but one factor involves related samples while the other factor involves independent samples, we should perform a ______.
A. Two-way within-subjects ANOVA
B. Two-way between-subjects ANOVA
C. Two-way mixed-design ANOVA
D. Two-way independent-related samples ANOVA
2: In a two-way ANOVA, the interaction effect is the ______.
A. Effect of changing the levels of one factor on the dependent scores
B. Effect of changing the levels of one factor on the dependent scores, ignoring all other factors in the study
C. Extent to which the influence one factor has on scores depends on the level of the other factor
D. Effect on the independent variables of changing the levels of a factor
3: A two-way ANOVA means that the experimental design includes ______.
A. Two independent variables
B. Two dependent variables
C. Two types of variance
D. All of these
4: How many conditions would there be in a factorial design with 2 levels of factor A and three levels of factor B?
A. 2
B. 3
C. 5
D. 6
5: A significant interaction effect indicates that ______.
A. The influence of one factor is not the same for each level of the other factor
B. The influence of one factor is the same for each level of the other factor
C. The relationship between one factor and the dependent variable differs from the relationship between the other factor and the dependent variable
D. The dependent variable differs depending on the level of a factor
6: A factorial design involves ______.
A. Measuring more than one dependent factor (variables)
B. Manipulating more than one independent factor (variable)
C. Measuring more than one dependent factor (variables) and manipulating more than one independent factor (variable)
D. None of these
7: A two-way ANOVA contains ______.
A. A main effect for each factor
B. A main effect for each factor and an interaction
C. An interaction for each factor and a main effect
D. An interaction for each factor
8: How many participants would be required for a completely randomized 4 × 5 between-subjects design with three observations per cell?
A. 18
B. 27
C. 20
D. 60
9: A(an) ______ is when an analysis of the data reveals a difference between the levels of any factor.
A. Source table
B. Interaction
C. Main effect
D. ANOVA
10: In a two-way ANOVA, an F involving a comparison among the level means of a factor is referred to as a test for the significance of ______.
A. A main effect
B. A factorial design
C. The interaction effect
D. A level effect
11: In a 2 × 2 design with 40 participants equally distributed across the conditions, what are ______ and ______.
A. = 1; = 10
B. = 2; = 10
C. = 1; = 40
D. = 2; = 20
12: Two variables interact when ______.
A. The effect of one independent variable depends on the level of the other independent variable
B. Both variables are affected equally by some third factor
C. There are no main effects
D. There are main effects
13: Researchers often use factorial designs because ______.
A. They allow us to see the interaction of factors
B. They more closely approximate the real world
C. Both allow us to see the interaction of factors and more closely approximate the real world
D. None of these.
14: A main effect indicates ______.
A. The mean differences among the levels of one variable
B. The mean differences among the levels of all variables
C. The mean difference between the two variables
D. None of these
15: An analysis of ____ with more than one factor or independent variable.
A. Regression
B. Variance
C. Correlation
D. All of these
16: In analysis of variance, when a factor or an independent variable has a significant effect upon the outcome variable is called
A. Main effect
B. Interaction effect
C. Linear effect
D. None of these
17: The outcome where the effect of one factor is differentiated across another factor is called
A. Main effect
B. Interaction effect
C. Linear effect
D. None of these
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Factorial Analysis of Variance in Statistics MCQs
