Question 1

What value appears in each identified cell in the following table? 
   
a. X11 
b. X23 
c. X41

Accepted Answer

Question 2

Unequal sample sizes in a factorial analysis of variance are

Accepted Answer

A)  no problem. 
B)  often difficult to interpret. 
C)  impossible to interpret. 
D)  easily explained by the use of simple effects. 
A)  no problem. 
B)  often difficult to interpret. 
C)  impossible to interpret. 
D)  easily explained by the use of simple effects.

Question 3

In graph I below, the most apparent simple effect is for the line represented by
 
​

Accepted Answer

A)  diamonds. 
B)  squares. 
C)  triangles. 
D)  It is unlikely for there to be a simple effect for any level of the independent variable. 
A)  diamonds. 
B)  squares. 
C)  triangles. 
D)  It is unlikely for there to be a simple effect for any level of the independent variable.

Question 4

In this graph we can see that there is
 
​

Accepted Answer

A)  a significant difference between Location 1 at time 1 and Location 2 at time 1. 
B)  an interaction between location and time. 
C)  a significant post hoc analysis. 
D)  a quadratic significant correlation. 
A)  a significant difference between Location 1 at time 1 and Location 2 at time 1. 
B)  an interaction between location and time. 
C)  a significant post hoc analysis. 
D)  a quadratic significant correlation.

Question 5

The mean difference in GPA based on gender and year in school is a main effect.

Accepted Answer

A) True 
 B)False

Question 6

A factorial analysis of variance involves more than one dependent variable.

Accepted Answer

A) True 
 B)False

Question 7

In a factorial design involving the sex of the participant and the sex of the experimenter's confederate

Accepted Answer

A)  there were multiple subjects in each cell of the design. 
B)  there were different subjects in each cell of the design. 
C)  all possible combinations of sex of subject and sex of confederate were represented. 
D)  all of the above 
A)  there were multiple subjects in each cell of the design. 
B)  there were different subjects in each cell of the design. 
C)  all possible combinations of sex of subject and sex of confederate were represented. 
D)  all of the above

Question 8

When we say that a measure is "not of theoretical interest" we mean that

Accepted Answer

A)  variability attributable to it should be removed from the denominator. 
B)  we can simply ignore that variable. 
C)  variability attributable to it should be included in the denominator. 
D)  there is no significant effect for that variable. 
A)  variability attributable to it should be removed from the denominator. 
B)  we can simply ignore that variable. 
C)  variability attributable to it should be included in the denominator. 
D)  there is no significant effect for that variable.

Question 9

The finding that women eat less in the company of men then when they are in the company of other women is a(n)

Accepted Answer

A)  simple effect. 
B)  interaction. 
C)  factorial effect. 
D)  main effect. 
A)  simple effect. 
B)  interaction. 
C)  factorial effect. 
D)  main effect.

Question 10

To calculate the magnitude of effect estimates for a factorial design, the methods are

Accepted Answer

A)  radically different from the methods used with a one-way design. 
B)  simple extensions of the methods used with a one-way design. 
C)  not possible to calculate. 
D)  only useful for estimating magnitude of effects for interactions, not main efforts. 
A)  radically different from the methods used with a one-way design. 
B)  simple extensions of the methods used with a one-way design. 
C)  not possible to calculate. 
D)  only useful for estimating magnitude of effects for interactions, not main efforts.

Question 11

-Calculate and explain ω 2 for treatment group from the previous problem.

Accepted Answer

ω ² = .029. Approximately 3% of

Question 12

When comparing differences in an experiment with two or more independent variables we should use a(n)

Accepted Answer

A)  one way ANOVA. 
B)  paired sample t-test. 
C)  R squared comparison. 
D)  factorial design. 
A)  one way ANOVA. 
B)  paired sample t-test. 
C)  R squared comparison. 
D)  factorial design.

Question 13

The difference between a one-way analysis of variance and a factorial analysis of variance is

Accepted Answer

A)  the presence of an interaction. 
B)  the presence of more than one main effect. 
C)  one-way analyses of variance have an error term, whereas factorial analyses do not. 
D)  both a and b 
A)  the presence of an interaction. 
B)  the presence of more than one main effect. 
C)  one-way analyses of variance have an error term, whereas factorial analyses do not. 
D)  both a and b

Question 14

If you have a significant interaction,

Accepted Answer

A)  at least one of the main effects will be nonsignificant. 
B)  both of the main effects will be nonsignificant. 
C)  at least one simple effect is likely, though not certain, to be significant. 
D)  the interaction doesn't suggest anything about simple effects. 
A)  at least one of the main effects will be nonsignificant. 
B)  both of the main effects will be nonsignificant. 
C)  at least one simple effect is likely, though not certain, to be significant. 
D)  the interaction doesn't suggest anything about simple effects.

What value appears in each identified cell in the following table? a. X₁₁ b. X₂₃ c. X₄₁

Unequal sample sizes in a factorial analysis of variance are

In graph I below, the most apparent simple effect is for the line represented by

In this graph we can see that there is

The mean difference in GPA based on gender and year in school is a main effect.

A factorial analysis of variance involves more than one dependent variable.

In a factorial design involving the sex of the participant and the sex of the experimenter's confederate

When we say that a measure is "not of theoretical interest" we mean that

The finding that women eat less in the company of men then when they are in the company of other women is a(n)

To calculate the magnitude of effect estimates for a factorial design, the methods are

-Calculate and explain ω ² for treatment group from the previous problem.

When comparing differences in an experiment with two or more independent variables we should use a(n)

The difference between a one-way analysis of variance and a factorial analysis of variance is

If you have a significant interaction,

Introduction

Basic Concepts

Displaying Data

Measures of Central Tendency

Measures of Variability

The Normal Distribution

Basic Concepts of Probability

Sampling Distributions and Hypothesis Testing

Correlation

Regression

Multiple Regression

Hypothesis Tests Applied to Means: One Sample

Hypothesis Tests Applied to Means: Two Related Samples

Hypothesis Tests Applied to Means: Two Independent Samples

Power

One-Way Analysis of Variance

Repeated-Measures Analysis of Variance

Chi-Square

Nonparametric and Resampling Statistical Tests

Meta-Analysis

Filters

Exam 17: Factorial Analysis of Variance

What value appears in each identified cell in the following table? a. X11 b. X23 c. X41

Unequal sample sizes in a factorial analysis of variance are

In graph I below, the most apparent simple effect is for the line represented by ​

In this graph we can see that there is ​

The mean difference in GPA based on gender and year in school is a main effect.

A factorial analysis of variance involves more than one dependent variable.

In a factorial design involving the sex of the participant and the sex of the experimenter's confederate

When we say that a measure is "not of theoretical interest" we mean that

The finding that women eat less in the company of men then when they are in the company of other women is a(n)

To calculate the magnitude of effect estimates for a factorial design, the methods are

-Calculate and explain ω 2 for treatment group from the previous problem.

When comparing differences in an experiment with two or more independent variables we should use a(n)

The difference between a one-way analysis of variance and a factorial analysis of variance is

If you have a significant interaction,

Introduction

Basic Concepts

Displaying Data

Measures of Central Tendency

Measures of Variability

The Normal Distribution

Basic Concepts of Probability

Sampling Distributions and Hypothesis Testing

Correlation

Regression

Multiple Regression

Hypothesis Tests Applied to Means: One Sample

Hypothesis Tests Applied to Means: Two Related Samples

Hypothesis Tests Applied to Means: Two Independent Samples

Power

One-Way Analysis of Variance

Repeated-Measures Analysis of Variance

Chi-Square

Nonparametric and Resampling Statistical Tests

Meta-Analysis

Filters

What value appears in each identified cell in the following table? a. X₁₁ b. X₂₃ c. X₄₁

In graph I below, the most apparent simple effect is for the line represented by

In this graph we can see that there is

-Calculate and explain ω ² for treatment group from the previous problem.