Question 1

What can be deduced about the sphericity of the shoe and shoe × platform variables?

Accepted Answer

A)  Both variables are non-significant, and therefore sphericity can be assumed. 
B)  Both variables are significant, and therefore sphericity can be assumed. 
C)  Both variables are non-significant, and therefore sphericity cannot be assumed. 
D)  Both variables are significant, and therefore sphericity cannot be assumed. 
A)  Both variables are non-significant, and therefore sphericity can be assumed. 
B)  Both variables are significant, and therefore sphericity can be assumed. 
C)  Both variables are non-significant, and therefore sphericity cannot be assumed. 
D)  Both variables are significant, and therefore sphericity cannot be assumed.

Question 2

Suppose you wished to investigate the force exerted on a force platform between men and women with three different types of footwear (barefoot, no cushioning, basic neutral shoe, BC; and complex cushioned neutral shoe, CCS). If you wished to compare the force exerted when running barefoot with the BC shoe and then the CCS shoe, what type of contrast might be appropriate?

Accepted Answer

A)  Simple 
B)  Repeated 
C)  Helmert 
D)  Deviation 
A)  Simple 
B)  Repeated 
C)  Helmert 
D)  Deviation

What can be deduced about the sphericity of the shoe and shoe × platform variables?

Why Is My Evil Lecturer Forcing Me to Learn Statistics

The Spine of Statistics

The Phoenix of Statistics

The Ibm Spss Statistics Environment

Exploring Data With Graphs

The Beast of Bias

Non-Parametric Models

Correlation

The Linear Model Regression

Comparing Two Means

Moderation, Mediation and Multicategory Predictors

Glm 1: Comparing Several Independent Means

Glm 2: Comparing Means Adjusted for Other Predictors Analysis of Covariance

Glm 3: Factorial Designs

Glm 4: Repeated-Measures Designs

Multivariate Analysis of Variance Manova

Exploratory Factor Analysis

Categorical Outcomes: Chi-Square and Loglinear Analysis

Categorical Outcomes: Logistic Regression

Multilevel Linear Models

Filters

Exam 16: Glm 5: Mixed Designs

What can be deduced about the sphericity of the shoe and shoe × platform variables?

Why Is My Evil Lecturer Forcing Me to Learn Statistics

The Spine of Statistics

The Phoenix of Statistics

The Ibm Spss Statistics Environment

Exploring Data With Graphs

The Beast of Bias

Non-Parametric Models

Correlation

The Linear Model Regression

Comparing Two Means

Moderation, Mediation and Multicategory Predictors

Glm 1: Comparing Several Independent Means

Glm 2: Comparing Means Adjusted for Other Predictors Analysis of Covariance

Glm 3: Factorial Designs

Glm 4: Repeated-Measures Designs

Multivariate Analysis of Variance Manova

Exploratory Factor Analysis

Categorical Outcomes: Chi-Square and Loglinear Analysis

Categorical Outcomes: Logistic Regression

Multilevel Linear Models

Filters