Question 1

Examine the table below. What do the z-scores (i.e. standardized residuals) for the two variables tell us?

Accepted Answer

A)  Athletes who were inspired by the London Olympics had a significant z-score. 
B)  Non-athletes who were inspired by the London Olympics had a significant z-score. 
C)  None of the z-scores were significant. 
D)  Athletes who were not inspired by the London Olympics had a significant z-score. 
A)  Athletes who were inspired by the London Olympics had a significant z-score. 
B)  Non-athletes who were inspired by the London Olympics had a significant z-score. 
C)  None of the z-scores were significant. 
D)  Athletes who were not inspired by the London Olympics had a significant z-score.

Question 2

Which of the following is the most appropriate measure of central tendency when working with categorical data?

Accepted Answer

A)  Mean 
B)  Mode 
C)  Median 
D)  None of the above are appropriate. 
A)  Mean 
B)  Mode 
C)  Median 
D)  None of the above are appropriate.

Question 3

What is the minimum number of observations required for the expected frequencies?

Accepted Answer

A)  1 
B)  5 
C)  10 
D)  15 
A)  1 
B)  5 
C)  10 
D)  15

Question 4

If the example above was developed to incorporate gender, athletic status and whether they were inspired by the London Olympics, how many main effects and interactions would exist?

Accepted Answer

A)  5 
B)  6 
C)  7 
D)  8 
A)  5 
B)  6 
C)  7 
D)  8

Examine the table below. What do the z-scores (i.e. standardized residuals) for the two variables tell us?

Which of the following is the most appropriate measure of central tendency when working with categorical data?

What is the minimum number of observations required for the expected frequencies?

If the example above was developed to incorporate gender, athletic status and whether they were inspired by the London Olympics, how many main effects and interactions would exist?

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

Glm 5: Mixed Designs

Multivariate Analysis of Variance Manova

Exploratory Factor Analysis

Categorical Outcomes: Logistic Regression

Multilevel Linear Models

Filters

Exam 19: Categorical Outcomes: Chi-Square and Loglinear Analysis

Examine the table below. What do the z-scores (i.e. standardized residuals) for the two variables tell us?

Which of the following is the most appropriate measure of central tendency when working with categorical data?

What is the minimum number of observations required for the expected frequencies?

If the example above was developed to incorporate gender, athletic status and whether they were inspired by the London Olympics, how many main effects and interactions would exist?

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

Glm 5: Mixed Designs

Multivariate Analysis of Variance Manova

Exploratory Factor Analysis

Categorical Outcomes: Logistic Regression

Multilevel Linear Models

Filters