Question 1

What is sphericity?

Accepted Answer

A)  An assumption that means the data distribution must be round. 
B)  The critical value area of the graph is round. 
C)  A way of rounding up the decimal points. 
D)  An assumption that means the data in each level should uncorrelated. 
A)  An assumption that means the data distribution must be round. 
B)  The critical value area of the graph is round. 
C)  A way of rounding up the decimal points. 
D)  An assumption that means the data in each level should uncorrelated.

Question 2

In a study undertaken by Alla et al. (2009) to determine whether exercise evoked neurological symptoms in healthy subjects, the following result was reported in respect of the interaction between level of exercise intensity and time: F(2, 118) = 23.94, p < 0.001 for intensity condition following exercise. (Source: Alla, S., Sullivan, S. J., McCrory, P., Schnieders, A. G., & Handcock, P. (2010). Does exercise evoke neurological symptoms in healthy subjects? Journal of Science and Medicine in Sport, 13(1), 24-26.) Which of the following statements best represents this result?

Accepted Answer

A)  The effect of intense exercise has little effect on players returning to their sport. 
B)  The effect of intense exercise needs to be acknowledged when making 'return to play' decisions for athletes.* 
C)  The effect of intense exercise increases over time. 
D)  None of the above. 
A)  The effect of intense exercise has little effect on players returning to their sport. 
B)  The effect of intense exercise needs to be acknowledged when making 'return to play' decisions for athletes.* 
C)  The effect of intense exercise increases over time. 
D)  None of the above.

Question 3

An experiment was carried out in which participants learned words in several conditions: no learning strategy, a verbal learning strategy, visual one and a verbal-visual one. The table below outlines the results from this experiment? What does this table indicate? Tests of Within-Subjects Effects
Measure: MEASURE_1

Accepted Answer

A)  There is too much sphericity in the model. 
B)  There are too many errors in the model. 
C)  The null hypothesis can be rejected. 
D)  The null hypothesis must be rejected. 
A)  There is too much sphericity in the model. 
B)  There are too many errors in the model. 
C)  The null hypothesis can be rejected. 
D)  The null hypothesis must be rejected.

Question 4

What is not a form of counterbalancing?

Accepted Answer

A)  Even-number algorithms 
B)  Odd-number algorithms 
C)  Random number algorithms 
D)  Heuristics 
A)  Even-number algorithms 
B)  Odd-number algorithms 
C)  Random number algorithms 
D)  Heuristics

What is sphericity?

What is not a form of counterbalancing?

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 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 15: Glm 4: Repeated-Measures Designs

What is sphericity?

What is not a form of counterbalancing?

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 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