Question 1

The simplest factorial design is a design.

Accepted Answer

A) 1 × 1 
B) 1 × 2 
C) 2 × 1 
D) 2 × 2 
A) 1 × 1 
B) 1 × 2 
C) 2 × 1 
D) 2 × 2

Question 2

When computed from a two-factor between-subjects analysis of variance, η2 is defined as the sum of squares associated with a factor divided by the sum of squares for the.

Accepted Answer

A) total 
B) total plus the df for total 
C) error 
D) error plus the df for error 
A) total 
B) total plus the df for total 
C) error 
D) error plus the df for error

Question 3

If MSA = 4.00, MSB = 10.00, MSA × B = 6.00, and MSError = 2.00 in a two-factor between-subjects analysis of variance, then Fobs for factor A = , Fobs for factor B = ,
And Fobs for the interaction of factors A and B =.

Accepted Answer

A) 3.00; 2.00; 5.00 
B) 2.00; 5.00; 3.00 
C) 2.00; 3.00; 5.00 
D) 5.00; 3.00; 2.00 
A) 3.00; 2.00; 5.00 
B) 2.00; 5.00; 3.00 
C) 2.00; 3.00; 5.00 
D) 5.00; 3.00; 2.00

Question 4

The degrees of freedom for factor B in a two-factor between-subjects analysis of variance are given by.

Accepted Answer

A) N - 1 
B) (a - 1)(b - 1) 
C) ab - 1 
D) b - 1 
A) N - 1 
B) (a - 1)(b - 1) 
C) ab - 1 
D) b - 1

Question 5

A factorial design is one in which two or more are simultaneously varied.

Accepted Answer

A) dependent variables 
B) levels of one independent variable 
C) independent variables 
D) extraneous variables 
A) dependent variables 
B) levels of one independent variable 
C) independent variables 
D) extraneous variables

Question 6

The F statistic for factor B in a two-factor between-subjects analysis of variance is formed by dividing MSB by.

Accepted Answer

A) MSError 
B) MSA 
C) MSA × B 
D) SSTotal 
A) MSError 
B) MSA 
C) MSA × B 
D) SSTotal

Question 7

The degrees of freedom for factor A in a two-factor between-subjects analysis of variance are given by.

Accepted Answer

A) N - 1 
B) (a - 1)(b - 1) 
C) a - 1 
D) a - 2 
A) N - 1 
B) (a - 1)(b - 1) 
C) a - 1 
D) a - 2

Question 8

A 2 × 2 between-subjects factorial design with ten scores per cell requires participants.

Accepted Answer

A) 10 
B) 20 
C) 40 
D) 80 
A) 10 
B) 20 
C) 40 
D) 80

Question 9

The difference . $X - \bar { X } _ { A B }$ in a two-factor between-subjects analysis of variance reflects the

Accepted Answer

A) main effect of factor A alone 
B) main effect of factor A plus sampling error 
C) total variation in the score 
D) within-cells error variation 
A) main effect of factor A alone 
B) main effect of factor A plus sampling error 
C) total variation in the score 
D) within-cells error variation

Question 10

The difference $X - \bar { X } _ { G }$ is involved in the computation of SS in a two-factor between-subjects analysis of variance.

Accepted Answer

A) Total 
B) A 
C) Error 
D) A × B 
A) Total 
B) A 
C) Error 
D) A × B

Question 11

A two-factor between-subjects analysis of variance is based upon the assumption that the in the populations sampled.

Accepted Answer

A) scores are symmetrical and bimodal 
B) means are equal 
C) means are normally distributed 
D) variances of scores are equal 
A) scores are symmetrical and bimodal 
B) means are equal 
C) means are normally distributed 
D) variances of scores are equal

Question 12

Suppose a 3 × 2 between-subjects design had 10 participants randomly assigned to each cell. The df for SSB are equal to and the df for SSError are equal to for the analysis of variance of this design.

Accepted Answer

A) 1; 59 
B) 2; 54 
C) 2; 59 
D) 1; 54 
A) 1; 59 
B) 2; 54 
C) 2; 59 
D) 1; 54

The simplest factorial design is a design.

When computed from a two-factor between-subjects analysis of variance, η2 is defined as the sum of squares associated with a factor divided by the sum of squares for the.

If MSA = 4.00, MSB = 10.00, MSA × B = 6.00, and MSError = 2.00 in a two-factor between-subjects analysis of variance, then Fobs for factor A = , Fobs for factor B = , And Fobs for the interaction of factors A and B =.

The degrees of freedom for factor B in a two-factor between-subjects analysis of variance are given by.

A factorial design is one in which two or more are simultaneously varied.

The F statistic for factor B in a two-factor between-subjects analysis of variance is formed by dividing MSB by.

The degrees of freedom for factor A in a two-factor between-subjects analysis of variance are given by.

A 2 × 2 between-subjects factorial design with ten scores per cell requires participants.

The difference . $X - \bar { X } _ { A B }$ in a two-factor between-subjects analysis of variance reflects the

The difference $X - \bar { X } _ { G }$ is involved in the computation of SS in a two-factor between-subjects analysis of variance.

A two-factor between-subjects analysis of variance is based upon the assumption that the in the populations sampled.

Suppose a 3 × 2 between-subjects design had 10 participants randomly assigned to each cell. The df for SSB are equal to and the df for SSError are equal to for the analysis of variance of this design.

Making Sense of Variability: an Introduction to Statistics

Statistics in the Context of Scientific Research

Looking at Data: Frequency Distributions and Graphs

Looking at Data: Measures of Central Tendency

Looking at Data: Measures of Variability

The Normal Distribution, Probability, and Standard Scores

Understanding Data: Using Statistics for Inference and Estimation

Is There Really a Difference Introduction to Statistical Hypothesis Testing

The Basics of Experimentation and Testing for a Difference Between Means

One-Factor Between-Subjects Analysis of Variance

One-Factor Within-Subjects Analysis of Variance

Correlation: Understanding Covariation

Regression Analysis: Predicting Linear Relationships

Nonparametric Tests

Filters

Exam 11: Two-Factor Between-Subjects Analysis of Variance

The simplest factorial design is a design.

When computed from a two-factor between-subjects analysis of variance, η2 is defined as the sum of squares associated with a factor divided by the sum of squares for the.

If MSA = 4.00, MSB = 10.00, MSA × B = 6.00, and MSError = 2.00 in a two-factor between-subjects analysis of variance, then Fobs for factor A = , Fobs for factor B = , And Fobs for the interaction of factors A and B =.

The degrees of freedom for factor B in a two-factor between-subjects analysis of variance are given by.

A factorial design is one in which two or more are simultaneously varied.

The F statistic for factor B in a two-factor between-subjects analysis of variance is formed by dividing MSB by.

The degrees of freedom for factor A in a two-factor between-subjects analysis of variance are given by.

A 2 × 2 between-subjects factorial design with ten scores per cell requires participants.

The difference . X−XˉABX - \bar { X } _ { A B }X−XˉAB​ in a two-factor between-subjects analysis of variance reflects the

The difference X−XˉGX - \bar { X } _ { G }X−XˉG​ is involved in the computation of SS in a two-factor between-subjects analysis of variance.

A two-factor between-subjects analysis of variance is based upon the assumption that the in the populations sampled.

Suppose a 3 × 2 between-subjects design had 10 participants randomly assigned to each cell. The df for SSB are equal to and the df for SSError are equal to for the analysis of variance of this design.

Making Sense of Variability: an Introduction to Statistics

Statistics in the Context of Scientific Research

Looking at Data: Frequency Distributions and Graphs

Looking at Data: Measures of Central Tendency

Looking at Data: Measures of Variability

The Normal Distribution, Probability, and Standard Scores

Understanding Data: Using Statistics for Inference and Estimation

Is There Really a Difference Introduction to Statistical Hypothesis Testing

The Basics of Experimentation and Testing for a Difference Between Means

One-Factor Between-Subjects Analysis of Variance

One-Factor Within-Subjects Analysis of Variance

Correlation: Understanding Covariation

Regression Analysis: Predicting Linear Relationships

Nonparametric Tests

Filters

The difference . $X - \bar { X } _ { A B }$ in a two-factor between-subjects analysis of variance reflects the

The difference $X - \bar { X } _ { G }$ is involved in the computation of SS in a two-factor between-subjects analysis of variance.