Question 1

Based on the answers provided in Q7, calculate the total sum of squares for the time-trial data.

Accepted Answer

A)  764.2 
B)  746.2 
C)  801.3 
D)  822.6 
A)  764.2 
B)  746.2 
C)  801.3 
D)  822.6

Question 2

An ANOVA works on the basis of comparing systematic and systematic variance, but how is this achieved?

Accepted Answer

A)  Systematic variance / unsystematic variance 
B)  Systematic variance × unsystematic variance 
C)  Unsystematic variance / systematic variance 
D)  Unsystematic variance - systematic variance 
A)  Systematic variance / unsystematic variance 
B)  Systematic variance × unsystematic variance 
C)  Unsystematic variance / systematic variance 
D)  Unsystematic variance - systematic variance

Question 3

An ANOVA works on the basis of comparing systematic and systematic variance, but how is this achieved?

Accepted Answer

A)  Systematic variance / unsystematic variance 
B)  Systematic variance × unsystematic variance 
C)  Unsystematic variance / systematic variance 
D)  Unsystematic variance - systematic variance 
A)  Systematic variance / unsystematic variance 
B)  Systematic variance × unsystematic variance 
C)  Unsystematic variance / systematic variance 
D)  Unsystematic variance - systematic variance

Question 4

Does an ANOVA test identify specifically where the differences exist between the groups?

Accepted Answer

A)  No 
B)  Yes 
C)  Yes, provided the data are normally distributed 
D)  Yes, provided the data are not normally distributed 
A)  No 
B)  Yes 
C)  Yes, provided the data are normally distributed 
D)  Yes, provided the data are not normally distributed

Question 5

For an ANOVA to be used, what is the minimum number of data sets required?

Accepted Answer

A)  2 
B)  3 
C)  4 
D)  5 
A)  2 
B)  3 
C)  4 
D)  5

Question 6

Using an F-distribution table, locate the critical value required to produce a p-value equal to .05.

Accepted Answer

A)  2.95 
B)  2.71 
C)  2.56 
D)  2.46 
A)  2.95 
B)  2.71 
C)  2.56 
D)  2.46

Based on the answers provided in Q7, calculate the total sum of squares for the time-trial data.

An ANOVA works on the basis of comparing systematic and systematic variance, but how is this achieved?

An ANOVA works on the basis of comparing systematic and systematic variance, but how is this achieved?

Does an ANOVA test identify specifically where the differences exist between the groups?

For an ANOVA to be used, what is the minimum number of data sets required?

Using an F-distribution table, locate the critical value required to produce a p-value equal to .05.

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 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: Chi-Square and Loglinear Analysis

Categorical Outcomes: Logistic Regression

Multilevel Linear Models

Filters

Exam 12: Glm 1: Comparing Several Independent Means

Based on the answers provided in Q7, calculate the total sum of squares for the time-trial data.

An ANOVA works on the basis of comparing systematic and systematic variance, but how is this achieved?

An ANOVA works on the basis of comparing systematic and systematic variance, but how is this achieved?

Does an ANOVA test identify specifically where the differences exist between the groups?

For an ANOVA to be used, what is the minimum number of data sets required?

Using an F-distribution table, locate the critical value required to produce a p-value equal to .05.

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 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: Chi-Square and Loglinear Analysis

Categorical Outcomes: Logistic Regression

Multilevel Linear Models

Filters