Question 1

Which of the following statements about the t-statistic in regression is not true?

Accepted Answer

A)  The t-statistic tests whether the regression coefficient, b, is equal to 0. 
B)  The t-statistic provides some idea of how well a predictor predicts the outcome variable. 
C)  The t-statistic can be used to see whether a predictor variable makes a statistically significant contribution to the regression model. 
D)  The t-statistic is equal to the regression coefficient divided by its standard deviation. 
A)  The t-statistic tests whether the regression coefficient, b, is equal to 0. 
B)  The t-statistic provides some idea of how well a predictor predicts the outcome variable. 
C)  The t-statistic can be used to see whether a predictor variable makes a statistically significant contribution to the regression model. 
D)  The t-statistic is equal to the regression coefficient divided by its standard deviation. D

Question 2

Using the model in equation (8.16), how many records would be sold if £29,000 was spent on brand advertising, the track was played 19 times on radio and the band were rated 7 on the attractiveness scale?

Accepted Answer

A)  2,461,660 records 
B)  2435 records 
C)  2488 records 
D)  2, 435, 050 records 
A)  2,461,660 records 
B)  2435 records 
C)  2488 records 
D)  2, 435, 050 records D

Question 3

If Forbes includes years of education and age to predict CEO salary, what would multicollinearity represent?

Accepted Answer

A)  High correlation between CEO age and years of education 
B)  A linear relationship of both predictor variables and CEO salary 
C)  Both predictor variables correlating with variables not included in the regression model 
D)  Independence between years of education and age 
A)  High correlation between CEO age and years of education 
B)  A linear relationship of both predictor variables and CEO salary 
C)  Both predictor variables correlating with variables not included in the regression model 
D)  Independence between years of education and age A

Question 4

An online retailer uses the number of website clicks to predict sales revenue for an online hair-replacement (wig) company. The R2 statistic represents?

Accepted Answer

A)  The percentage of variance in the predictor (clicks) variable accounted for by the outcome (sales revenue) variable. 
B)  The proportion of variance in the outcome variable (sales revenue) accounted for by the predictor variable (clicks). 
C)  The proportion of variance in the predictor variable (clicks) accounted for by unknown variables. 
D)  The percentage of variance in the outcome variable (sales revenue) accounted for by unknown variables. 
A)  The percentage of variance in the predictor (clicks) variable accounted for by the outcome (sales revenue) variable. 
B)  The proportion of variance in the outcome variable (sales revenue) accounted for by the predictor variable (clicks). 
C)  The proportion of variance in the predictor variable (clicks) accounted for by unknown variables. 
D)  The percentage of variance in the outcome variable (sales revenue) accounted for by unknown variables.

Question 5

Which regression assumption does the Durbin-Watson statistic assess?

Accepted Answer

A)  Linearity 
B)  Independence of errors 
C)  Homoscedasticity 
D)  Multicollinearity 
A)  Linearity 
B)  Independence of errors 
C)  Homoscedasticity 
D)  Multicollinearity

Question 6

Forbes has modelled CEO salary by age for an exclusive feature in the magazine. Which of the following statements is not true about outliers in the model?

Accepted Answer

A)  Outliers are values where CEO salary against age is very different from others in the data set 
B)  Outliers bias the mean. 
C)  Outliers bias regression parameters (if included in the model). 
D)  Outliers only represent influential CEOs in the data set. 
A)  Outliers are values where CEO salary against age is very different from others in the data set 
B)  Outliers bias the mean. 
C)  Outliers bias regression parameters (if included in the model). 
D)  Outliers only represent influential CEOs in the data set.

Question 7

A business analyst wanted to predict the success of a government intervention in failing firms, predicted by a categorical variable, 'duration of financial difficulty prior to the intervention'. The predictor variable had four categories: less than 6 months, 6-12 months, 1-2 years, more than 2 years. They needed to code these variables into dummy variables for the regression using less than 6 months as their control category. Which of the following represents the correct coding scheme?

Accepted Answer

A)    
B)    
C)    
D)    
A)    
B)    
C)    
D)

Question 8

The difficulty with using one regression equation to predict values in a different set of data is called?

Accepted Answer

A)  Shrinkage 
B)  Contraction 
C)  Reduction 
D)  Washing 
A)  Shrinkage 
B)  Contraction 
C)  Reduction 
D)  Washing

Question 9

Which of the following statements about the F-ratio is true?

Accepted Answer

A)  The F-ratio is the ratio of variance explained by the model to the error in the model. 
B)  The F-ratio is the ratio of variance explained by the model to the total variance in the outcome variable. 
C)  The F-ratio is the ratio of error variance to total variance. 
D)  The F-ratio is the proportion of variance explained by the regression model. 
A)  The F-ratio is the ratio of variance explained by the model to the error in the model. 
B)  The F-ratio is the ratio of variance explained by the model to the total variance in the outcome variable. 
C)  The F-ratio is the ratio of error variance to total variance. 
D)  The F-ratio is the proportion of variance explained by the regression model.

Question 10

Management Research magazine has recently published an article on discrete categories. Which of the following strategies for modelling discrete data do you think they suggest?

Accepted Answer

A)  Stupid variables 
B)  Dummy variables 
C)  Imitation variables 
D)  Faking variables 
A)  Stupid variables 
B)  Dummy variables 
C)  Imitation variables 
D)  Faking variables

Question 11

Which of these statements is not true?

Accepted Answer

A)  If the average variance inflation factor is greater than 1, the regression model might be biased. 
B)  Tolerance values above 0.2 may indicate multicollinearity in the data. 
C)  Multicollinearity in the data is shown by a VIF (variance inflation factor) greater than 10. 
D)  The tolerance value is calculated by 1 / VIF (variance inflation factor) 
A)  If the average variance inflation factor is greater than 1, the regression model might be biased. 
B)  Tolerance values above 0.2 may indicate multicollinearity in the data. 
C)  Multicollinearity in the data is shown by a VIF (variance inflation factor) greater than 10. 
D)  The tolerance value is calculated by 1 / VIF (variance inflation factor)

Question 12

The distances of cases from the model mean are called?

Accepted Answer

A)  Leverage values 
B)  Hat values 
C)  Standard distances. 
D)  Mahalanobis distances 
A)  Leverage values 
B)  Hat values 
C)  Standard distances. 
D)  Mahalanobis distances

Question 13

The following graph shows evidence of?

Accepted Answer

A)  Heteroscedasticity 
B)  Non-linearity 
C)  Heteroscedasticity and non-linearity 
D)  Regression assumptions that have been satisfied. 
A)  Heteroscedasticity 
B)  Non-linearity 
C)  Heteroscedasticity and non-linearity 
D)  Regression assumptions that have been satisfied.

Question 14

Which of these problems arise as collinearity increases?

Accepted Answer

A)  Untrustworthy beta coefficients. 
B)  The size of R is constrained 
C)  It is more difficult to estimate the individual importance of a predictor 
D)  All of the above. 
A)  Untrustworthy beta coefficients. 
B)  The size of R is constrained 
C)  It is more difficult to estimate the individual importance of a predictor 
D)  All of the above.

Question 15

Which of the following is not a reason for multicollinearity being a problem in regression?

Accepted Answer

A)  It limits the size of R. 
B)  It makes it difficult to assess the importance of individual predictors. 
C)  It leads to unstable regression coefficients. 
D)  It creates heteroscedasticity in the data. 
A)  It limits the size of R. 
B)  It makes it difficult to assess the importance of individual predictors. 
C)  It leads to unstable regression coefficients. 
D)  It creates heteroscedasticity in the data.

Which of the following statements about the t-statistic in regression is not true?

Using the model in equation (8.16), how many records would be sold if £29,000 was spent on brand advertising, the track was played 19 times on radio and the band were rated 7 on the attractiveness scale?

If Forbes includes years of education and age to predict CEO salary, what would multicollinearity represent?

An online retailer uses the number of website clicks to predict sales revenue for an online hair-replacement (wig) company. The R² statistic represents?

Which regression assumption does the Durbin-Watson statistic assess?

Forbes has modelled CEO salary by age for an exclusive feature in the magazine. Which of the following statements is not true about outliers in the model?

The difficulty with using one regression equation to predict values in a different set of data is called?

Which of the following statements about the F-ratio is true?

Management Research magazine has recently published an article on discrete categories. Which of the following strategies for modelling discrete data do you think they suggest?

Which of these statements is not true?

The distances of cases from the model mean are called?

The following graph shows evidence of?

Which of these problems arise as collinearity increases?

Which of the following is not a reason for multicollinearity being a problem in regression?

Why Is My Evil Lecturer Forcing Me to Learn Statistic

The Spine of Statistics

The Phoenix of Statistics

The Ibm Spss Statistics Environment

Exploring Data With Graphs

Non-Parametric Models

Correlation

Comparing

Moderation, Mediation and Multicategory Predictors

Comparing Several Means

Analysis of Covariance

Factorial Anova

Repeated-Measures Designs

Mixed Design Anova

Multiple Analysis of Variance Manova

Exploratory Factor Analysis

Categorical Data

Logistic Regression

Multilevel Linear Models

Filters

Exam 9: Regression

Which of the following statements about the t-statistic in regression is not true?

Using the model in equation (8.16), how many records would be sold if £29,000 was spent on brand advertising, the track was played 19 times on radio and the band were rated 7 on the attractiveness scale?

If Forbes includes years of education and age to predict CEO salary, what would multicollinearity represent?

An online retailer uses the number of website clicks to predict sales revenue for an online hair-replacement (wig) company. The R2 statistic represents?

Which regression assumption does the Durbin-Watson statistic assess?

Forbes has modelled CEO salary by age for an exclusive feature in the magazine. Which of the following statements is not true about outliers in the model?

The difficulty with using one regression equation to predict values in a different set of data is called?

Which of the following statements about the F-ratio is true?

Management Research magazine has recently published an article on discrete categories. Which of the following strategies for modelling discrete data do you think they suggest?

Which of these statements is not true?

The distances of cases from the model mean are called?

The following graph shows evidence of?

Which of these problems arise as collinearity increases?

Which of the following is not a reason for multicollinearity being a problem in regression?

Why Is My Evil Lecturer Forcing Me to Learn Statistic

The Spine of Statistics

The Phoenix of Statistics

The Ibm Spss Statistics Environment

Exploring Data With Graphs

Non-Parametric Models

Correlation

Comparing

Moderation, Mediation and Multicategory Predictors

Comparing Several Means

Analysis of Covariance

Factorial Anova

Repeated-Measures Designs

Mixed Design Anova

Multiple Analysis of Variance Manova

Exploratory Factor Analysis

Categorical Data

Logistic Regression

Multilevel Linear Models

Filters

An online retailer uses the number of website clicks to predict sales revenue for an online hair-replacement (wig) company. The R² statistic represents?