Factorial Analysis of Variance statistics MCQs
Factorial Analysis of Variance statistics MCQs
Welcome to MCQss.com, your comprehensive resource for multiple-choice questions on Factorial Analysis of Variance (ANOVA). Factorial ANOVA is a powerful statistical technique used to analyze the effects of multiple independent variables on a dependent variable.
Engaging with the Factorial ANOVA MCQs provided on MCQss.com will deepen your understanding of the factorial design, the impact of independent variables on the dependent variable, and the interplay between factors. By practicing these questions, you will enhance your ability to analyze and interpret factorial designs, make informed statistical decisions, and draw meaningful conclusions from your data.
1: A design in which there is more than one factor or categorical predictor variable is known as _______ .
A. Counterbalancing
B. Latin Square
C. Factorial Design
D. Mauchly’s Sphericity Test
2: A factorial design is completely crossed when each level of the A factor is paired with each level of the B factor is known as ________ .
A. Counterbalancing
B. Latin Square
C. Completely Crossed
D. Mauchly’s Sphericity Test
3: Each group in an analysis of variance corresponds to a level of the factor is known as _______ .
A. Counterbalancing
B. Latin Square
C. Levels of a Factor
D. Mauchly’s Sphericity Test
4: Orthogonal Factorial ANOVA is a factorial design in which the numbers of cases in the cells are equal .
A. True
B. False
5: Interaction Effect is a pattern of cell means in a factorial ANOVA that is different from what would be predicted by summing the grand mean .
A. True
B. False
6: An analysis in which group differences on means for one continuous Y outcome variable are assessed is known as:
A. Multivariate Analysis of Variance
B. Analysis of Covariance
C. Mixed Models
D. None of these
7: ANCOVA stands for analysis of covariance.
A. True
B. False
8: This is a multivariate generalization of analysis of variance. Like analysis of variance, it involves comparisons of means across groups is called _________ .
A. Multivariate Analysis of Variance
B. Analysis of Covariance
C. Mixed Models
D. None of these
9: MANOVA is known as multivariate analysis of variance.
A. True
B. False
10: Mixed models refers to analyses of variance that include both within-S and between-S factors.
A. True
B. False
11: A factor in an analysis of variance is “fixed” if the levels of the factor that are included in the study include all the possible levels for that factor is known as:
A. Random Factor
B. Weighted Mean
C. Fixed Factor
D. None of these
12: An analysis of variance is considered random if the levels included in the study represent an extremely small proportion of all the possible levels for that factor is called __________ .
A. Random Factor
B. Weighted Mean
C. Fixed Factor
D. None of these
13: [(n1M1) + (n2M2)]/(n1 + n2) = ?
A. Random Factor
B. Weighted Mean
C. Fixed Factor
D. None of these
14: A method of regression in which all predictor variables are entered into the equation at one step is known as:
A. Standard Regression
B. Sum of Squares
C. Simultaneous Regression
D. None of these
15: A method of entry of predictors for multiple regression; in simultaneous regression, all predictors are entered at one step is called _____________ .
A. Standard Regression
B. Sum of Squares
C. Simultaneous Regression
D. None of these
16: ______________ is a method of variance partitioning in the SPSS GLM procedure that is essentially equivalent to the method of variance partitioning in sequential or hierarchical multiple regression.
A. Standard Regression
B. Sum of Squares
C. Simultaneous Regression
D. None of these
17: Partition of Variance is the variability of scores (as indexed by their sum of squares) can be partitioned or separated into _________ parts.
A. 2
B. 3
C. 1
D. 4
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Factorial Analysis of Variance statistics MCQs
