Question 1

What does m in a straight-line equation represent?

Accepted Answer

A)  The gradient of the straight line 
B)  The predictor variable 
C)  The intercept on the y-axis 
D)  The outcome variable 
A)  The gradient of the straight line 
B)  The predictor variable 
C)  The intercept on the y-axis 
D)  The outcome variable A

Question 2

What does the term 'residual sum of errors' (SSR) represent?

Accepted Answer

A)  The extent to which the line of best fit reflects the data 
B)  The degree of covariance that exists between the data 
C)  The measure of sphercity regarding the variables of concern 
D)  All of the above are appropriate. 
A)  The extent to which the line of best fit reflects the data 
B)  The degree of covariance that exists between the data 
C)  The measure of sphercity regarding the variables of concern 
D)  All of the above are appropriate. A

Question 3

You run a correlation matrix of the seven different skinfold sites and obtain an R value of .87 for the abdominal and subscapular sites and a variance inflation factor (VIF) of 0.1. What would you deduce from these findings?

Accepted Answer

A)  A high degree of collinearity is likely between these two skinfold sites. 
B)  A low degree of collinearity is likely between these two skinfold sites. 
C)  A moderate degree of collinearity is likely between these two skinfold sites. 
D)  These figures make it difficult to deduce firm conclusions. 
A)  A high degree of collinearity is likely between these two skinfold sites. 
B)  A low degree of collinearity is likely between these two skinfold sites. 
C)  A moderate degree of collinearity is likely between these two skinfold sites. 
D)  These figures make it difficult to deduce firm conclusions. A

Question 4

What happens to the line of best fit if participant 4 scored 22, instead of 95, and participant 17 scored 20 as opposed to 90 in the diving competition?

Accepted Answer

A)  The line of best fit has become flatter. 
B)  The line of best fit has become steeper. 
C)  The line of best fit has the same angle but is generally above the observations. 
D)  The line is relatively unaffected by the change in data. 
A)  The line of best fit has become flatter. 
B)  The line of best fit has become steeper. 
C)  The line of best fit has the same angle but is generally above the observations. 
D)  The line is relatively unaffected by the change in data.

Question 5

Which of the following are assumptions of multiple linear regression?

Accepted Answer

A)  A sample is representative of its population and the observations are independent. 
B)  Linearity exists within the data. 
C)  Normal distribution. 
D)  All of the above. 
A)  A sample is representative of its population and the observations are independent. 
B)  Linearity exists within the data. 
C)  Normal distribution. 
D)  All of the above.

Question 6

What does c in a straight line equation represent?

Accepted Answer

A)  The gradient of the straight line 
B)  The predictor variable 
C)  The intercept on the y-axis 
D)  The outcome variable 
A)  The gradient of the straight line 
B)  The predictor variable 
C)  The intercept on the y-axis 
D)  The outcome variable

Question 7

You determine an effect size from a study to be .04. How would this effect be categorized?

Accepted Answer

A)  Very weak effect 
B)  Medium effect 
C)  Medium to strong effect 
D)  Very strong effect 
A)  Very weak effect 
B)  Medium effect 
C)  Medium to strong effect 
D)  Very strong effect

Question 8

If there are key skinfold sites known to the researcher that enabled percentage body fat to be predicted, which regression method(s) should be chosen?

Accepted Answer

A)  Hierarchial (blockwise entry) 
B)  Forced entry(Enter) 
C)  Stepwise 
D)  Backward 
A)  Hierarchial (blockwise entry) 
B)  Forced entry(Enter) 
C)  Stepwise 
D)  Backward

Question 9

What was the adjusted R2 value for the diving data?

Accepted Answer

A)  .329 
B)  .331 
C)  .292 
D)  .259 
A)  .329 
B)  .331 
C)  .292 
D)  .259

Question 10

Why is the sample size so important to statistical analysis, in this case during regression analysis?

Accepted Answer

A)  It provides a more reliable regression model. 
B)  It provides additional assurance that predictors are from a normally distributed data set. 
C)  It increases the chances of detecting a difference if one exists. 
D)  All of the above. 
A)  It provides a more reliable regression model. 
B)  It provides additional assurance that predictors are from a normally distributed data set. 
C)  It increases the chances of detecting a difference if one exists. 
D)  All of the above.

Question 11

Percentage body fat cannot be measured directly, so it has to be predicted from a series of skinfold measures. Suppose seven sites were measured (triceps, chest, midauxillary, subscapular, suprailiac, abdominal and thigh). How many participants should be recruited for a multiple regression to be performed?

Accepted Answer

A)  105 
B)  155 
C)  85 
D)  65 
A)  105 
B)  155 
C)  85 
D)  65

Question 12

Typically, research studies in sports science tend to recruit fairly small sample groups (less than 20), but what magnitude of effect can random data have on a data set?

Accepted Answer

A)  Strong effect 
B)  Weak effect 
C)  No measurable effect 
D)  Weak to medium effect 
A)  Strong effect 
B)  Weak effect 
C)  No measurable effect 
D)  Weak to medium effect

Question 13

Suppose the abdominal and subscapular skinfold sites had a high degree of collinearity. What are the implications of this when attempting to predict percentage body fat?

Accepted Answer

A)  Increased standard errors of the b coefficient. 
B)  It limits the R value as the predictor variables account for the same variance in the outcome variable (i.e. percentage body fat). 
C)  It becomes difficult to decide which variable to include. 
D)  All of the above. 
A)  Increased standard errors of the b coefficient. 
B)  It limits the R value as the predictor variables account for the same variance in the outcome variable (i.e. percentage body fat). 
C)  It becomes difficult to decide which variable to include. 
D)  All of the above.

Question 14

Using the equation identified in Q2, calculate the potential score in a diving competition if they have amassed 250 hours of training in the 12 months leading up to the competition. Assume m = .1016 and c = 22.5.

Accepted Answer

A)  48 points 
B)  52 points 
C)  58 points 
D)  60 points 
A)  48 points 
B)  52 points 
C)  58 points 
D)  60 points

Question 15

What purpose does the adjusted R2 value serve?

Accepted Answer

A)  The variance in the outcome variable if the model was drawn from the population of the sample. 
B)  The variance between the predictor and outcome variable. 
C)  This is used to correct for the covariance. 
D)  It more accurately reflects the sample data. 
A)  The variance in the outcome variable if the model was drawn from the population of the sample. 
B)  The variance between the predictor and outcome variable. 
C)  This is used to correct for the covariance. 
D)  It more accurately reflects the sample data.

Question 16

What does hierarchical regression refer to?

Accepted Answer

A)  Known predictors of the outcome variable are entered first. 
B)  Known predictors of the outcome variable are entered last. 
C)  Known predictors of the outcome variable are entered simultaneously. 
D)  Variables are entered based on a mathematical formula. 
A)  Known predictors of the outcome variable are entered first. 
B)  Known predictors of the outcome variable are entered last. 
C)  Known predictors of the outcome variable are entered simultaneously. 
D)  Variables are entered based on a mathematical formula.

Question 17

Which procedure could be used to determine whether the residuals from the proposed model are independent?

Accepted Answer

A)  Durbin-Watson 
B)  Cook's distance 
C)  Mahalanobis distance 
D)  None of the above are appropriate 
A)  Durbin-Watson 
B)  Cook's distance 
C)  Mahalanobis distance 
D)  None of the above are appropriate

Question 18

Having obtained a scatterplot to inspect the data, you suspect that the results for participants 4 and 17 are outliers. What should you do?

Accepted Answer

A)  Remove the cases so that the model is more representative of the majority of observations. 
B)  Perform a series of diagnostic tests on the data such as Cook's distance or Mahalanobis distance. 
C)  Leave the data points in and incorporate the Fick reducer variable. 
D)  Rerun the analysis without the observations in to see how the regression model is affected. 
A)  Remove the cases so that the model is more representative of the majority of observations. 
B)  Perform a series of diagnostic tests on the data such as Cook's distance or Mahalanobis distance. 
C)  Leave the data points in and incorporate the Fick reducer variable. 
D)  Rerun the analysis without the observations in to see how the regression model is affected.

Question 19

The difference between each observation (i.e. hours of training and competition score) and the model fitted to the data (i.e. all observations) is known as

Accepted Answer

A)  Residual 
B)  Difference 
C)  Offset 
D)  Disparity 
A)  Residual 
B)  Difference 
C)  Offset 
D)  Disparity

Question 20

Having developed a statistical model to predict percentage body fat, what is the purpose of conducting cross-validation?

Accepted Answer

A)  To test the accuracy of the prediction. 
B)  To test the model on a different population. 
C)  To evaluate the covariance within the model. 
D)  To measure the degree of difference in the residuals. 
A)  To test the accuracy of the prediction. 
B)  To test the model on a different population. 
C)  To evaluate the covariance within the model. 
D)  To measure the degree of difference in the residuals.

What does m in a straight-line equation represent?

What does the term 'residual sum of errors' (SS_R) represent?

You run a correlation matrix of the seven different skinfold sites and obtain an R value of .87 for the abdominal and subscapular sites and a variance inflation factor (VIF) of 0.1. What would you deduce from these findings?

What happens to the line of best fit if participant 4 scored 22, instead of 95, and participant 17 scored 20 as opposed to 90 in the diving competition?

Which of the following are assumptions of multiple linear regression?

What does c in a straight line equation represent?

You determine an effect size from a study to be .04. How would this effect be categorized?

If there are key skinfold sites known to the researcher that enabled percentage body fat to be predicted, which regression method(s) should be chosen?

What was the adjusted R² value for the diving data?

Why is the sample size so important to statistical analysis, in this case during regression analysis?

Typically, research studies in sports science tend to recruit fairly small sample groups (less than 20), but what magnitude of effect can random data have on a data set?

Suppose the abdominal and subscapular skinfold sites had a high degree of collinearity. What are the implications of this when attempting to predict percentage body fat?

Using the equation identified in Q2, calculate the potential score in a diving competition if they have amassed 250 hours of training in the 12 months leading up to the competition. Assume m = .1016 and c = 22.5.

What purpose does the adjusted R² value serve?

What does hierarchical regression refer to?

Which procedure could be used to determine whether the residuals from the proposed model are independent?

Having obtained a scatterplot to inspect the data, you suspect that the results for participants 4 and 17 are outliers. What should you do?

The difference between each observation (i.e. hours of training and competition score) and the model fitted to the data (i.e. all observations) is known as

Having developed a statistical model to predict percentage body fat, what is the purpose of conducting cross-validation?

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

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: Chi-Square and Loglinear Analysis

Categorical Outcomes: Logistic Regression

Multilevel Linear Models

Filters

Exam 9: The Linear Model Regression

What does m in a straight-line equation represent?

What does the term 'residual sum of errors' (SSR) represent?

You run a correlation matrix of the seven different skinfold sites and obtain an R value of .87 for the abdominal and subscapular sites and a variance inflation factor (VIF) of 0.1. What would you deduce from these findings?

What happens to the line of best fit if participant 4 scored 22, instead of 95, and participant 17 scored 20 as opposed to 90 in the diving competition?

Which of the following are assumptions of multiple linear regression?

What does c in a straight line equation represent?

You determine an effect size from a study to be .04. How would this effect be categorized?

If there are key skinfold sites known to the researcher that enabled percentage body fat to be predicted, which regression method(s) should be chosen?

What was the adjusted R2 value for the diving data?

Why is the sample size so important to statistical analysis, in this case during regression analysis?

Typically, research studies in sports science tend to recruit fairly small sample groups (less than 20), but what magnitude of effect can random data have on a data set?

Suppose the abdominal and subscapular skinfold sites had a high degree of collinearity. What are the implications of this when attempting to predict percentage body fat?

Using the equation identified in Q2, calculate the potential score in a diving competition if they have amassed 250 hours of training in the 12 months leading up to the competition. Assume m = .1016 and c = 22.5.

What purpose does the adjusted R2 value serve?

What does hierarchical regression refer to?

Which procedure could be used to determine whether the residuals from the proposed model are independent?

Having obtained a scatterplot to inspect the data, you suspect that the results for participants 4 and 17 are outliers. What should you do?

The difference between each observation (i.e. hours of training and competition score) and the model fitted to the data (i.e. all observations) is known as

Having developed a statistical model to predict percentage body fat, what is the purpose of conducting cross-validation?

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

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: Chi-Square and Loglinear Analysis

Categorical Outcomes: Logistic Regression

Multilevel Linear Models

Filters

What does the term 'residual sum of errors' (SS_R) represent?

What was the adjusted R² value for the diving data?

What purpose does the adjusted R² value serve?