Business Analytics, 3e James Evans Test
Bank 2025/2026
If an independent variable has a p-value of 0.07, which of the following could represent
the Lower 95% and the Upper 95% for that variable? - CORRECT ANSWER-Should
cross 0
The p-value, 0.07, is greater than 0.05 so the independent variable is not significant at
the 5% significance level. Therefore, the 95% confidence interval for the coefficient of
the independent variable must include zero. The interval between -14.52 and 3.25
contains zero.
What does R-square indicate? - CORRECT ANSWER-R-square indicates what
percentage of the variability in the dependent variable is explained by the regression
line
multicollinearity - CORRECT ANSWER-Multicollinearity occurs when two or more
independent variables are highly correlated
What is the difference between analyzing residual plots for single variable regression
models and analyzing residual plots for multiple regression models - CORRECT
ANSWER-Single variable regression plots give insight into the gross relationship
between the independent and dependent variable, whereas multiple regression plots
give insight into the net relationship, controlling for the other independent variables
included in the regression model.
Multicollinearity is usually not an issue when the regression model is only being used for
forecasting
If the street fair organizer wanted to compare the explanatory power of the original
model and the following new regression model, which value should he consult for the
new model? - CORRECT ANSWER-It is important to use the Adjusted R2 to compare
two regression models that have a different number of independent variables.
Previous Question Question 3 of 20 Next Question
An airport shuttle company forecasts the number of hours its drivers will work based on
the distance to be driven (in miles) and the number of jobs (each job requires the pickup
and drop-off of one set of passengers) using the following regression equation:
, Travel time=-0.60+0.05(distance)+0.75(number of jobs)
On a given day, Victor and Sofia drive approximately the same distance but Sofia has
two more jobs than Victor. If Victor worked for 4 hours, for how long can the company
expect Sofia to work? - CORRECT ANSWER-5.5
The only difference between the workloads of the two drivers is the number of jobs each
has; Sofia has two additional jobs. Therefore the company can expect Sofia to work the
four hours Victor worked, plus an additional 0.75 hours for each of the two additional
jobs, that is, 4+0.75(2)=5.5 hours.
A sporting goods store manager wants to forecast annual sneaker revenues based on
the type of sport (running, tennis, or walking), color (red, blue, white, black, or violet)
and its target audience (men or women). How many independent variables should the
manager include in her multiple regression analysis? - CORRECT ANSWER-Sales
revenue is the dependent variable. Type of sport, color, and target audience are
categorical variables which must be represented using dummy variables. Recall that it is
necessary to use one fewer dummy variables than the number of options in a category.
Thus, type of sport should be represented by 3-1=2 dummy variables, color should be
represented by 5-1=4 dummy variables, and target audience should be represented by
2-1=1 dummy variables, for a total of 2+4+1=7 independent variables.
single variable linear regression - CORRECT ANSWER-to investigate the relationship
between a dependent variable and one independent variable.
A coefficient in a single variable linear regression characterizes the gross relationship
between the independent variable and the dependent variable.
multiple regression - CORRECT ANSWER-investigate the relationship between a
dependent variable and multiple independent variables.
ŷ =a+b1x1+b2x2+...+bkxk
Coefficients in multiple regression characterize relationships that are net with respect to
the independent variables included in the model but gross with respect to all omitted
independent variables.
R-squared vs adjusted R-squared - CORRECT ANSWER-Because R2 never decreases
when independent variables are added to a regression, it is important to multiply it by an
adjustment factor when assessing and comparing the fit of a multiple regression model.
This adjustment factor compensates for the increase in R2 that results solely from
increasing the number of independent variables.
Adjusted R2 is provided in the regression output.
It is particularly important to look at Adjusted R2, rather than R2, when comparing
regression models with different numbers of independent variables.
multicollinearity - CORRECT ANSWER-Multicollinearity occurs when there is a strong
linear relationship among two or more of the independent variables.
Bank 2025/2026
If an independent variable has a p-value of 0.07, which of the following could represent
the Lower 95% and the Upper 95% for that variable? - CORRECT ANSWER-Should
cross 0
The p-value, 0.07, is greater than 0.05 so the independent variable is not significant at
the 5% significance level. Therefore, the 95% confidence interval for the coefficient of
the independent variable must include zero. The interval between -14.52 and 3.25
contains zero.
What does R-square indicate? - CORRECT ANSWER-R-square indicates what
percentage of the variability in the dependent variable is explained by the regression
line
multicollinearity - CORRECT ANSWER-Multicollinearity occurs when two or more
independent variables are highly correlated
What is the difference between analyzing residual plots for single variable regression
models and analyzing residual plots for multiple regression models - CORRECT
ANSWER-Single variable regression plots give insight into the gross relationship
between the independent and dependent variable, whereas multiple regression plots
give insight into the net relationship, controlling for the other independent variables
included in the regression model.
Multicollinearity is usually not an issue when the regression model is only being used for
forecasting
If the street fair organizer wanted to compare the explanatory power of the original
model and the following new regression model, which value should he consult for the
new model? - CORRECT ANSWER-It is important to use the Adjusted R2 to compare
two regression models that have a different number of independent variables.
Previous Question Question 3 of 20 Next Question
An airport shuttle company forecasts the number of hours its drivers will work based on
the distance to be driven (in miles) and the number of jobs (each job requires the pickup
and drop-off of one set of passengers) using the following regression equation:
, Travel time=-0.60+0.05(distance)+0.75(number of jobs)
On a given day, Victor and Sofia drive approximately the same distance but Sofia has
two more jobs than Victor. If Victor worked for 4 hours, for how long can the company
expect Sofia to work? - CORRECT ANSWER-5.5
The only difference between the workloads of the two drivers is the number of jobs each
has; Sofia has two additional jobs. Therefore the company can expect Sofia to work the
four hours Victor worked, plus an additional 0.75 hours for each of the two additional
jobs, that is, 4+0.75(2)=5.5 hours.
A sporting goods store manager wants to forecast annual sneaker revenues based on
the type of sport (running, tennis, or walking), color (red, blue, white, black, or violet)
and its target audience (men or women). How many independent variables should the
manager include in her multiple regression analysis? - CORRECT ANSWER-Sales
revenue is the dependent variable. Type of sport, color, and target audience are
categorical variables which must be represented using dummy variables. Recall that it is
necessary to use one fewer dummy variables than the number of options in a category.
Thus, type of sport should be represented by 3-1=2 dummy variables, color should be
represented by 5-1=4 dummy variables, and target audience should be represented by
2-1=1 dummy variables, for a total of 2+4+1=7 independent variables.
single variable linear regression - CORRECT ANSWER-to investigate the relationship
between a dependent variable and one independent variable.
A coefficient in a single variable linear regression characterizes the gross relationship
between the independent variable and the dependent variable.
multiple regression - CORRECT ANSWER-investigate the relationship between a
dependent variable and multiple independent variables.
ŷ =a+b1x1+b2x2+...+bkxk
Coefficients in multiple regression characterize relationships that are net with respect to
the independent variables included in the model but gross with respect to all omitted
independent variables.
R-squared vs adjusted R-squared - CORRECT ANSWER-Because R2 never decreases
when independent variables are added to a regression, it is important to multiply it by an
adjustment factor when assessing and comparing the fit of a multiple regression model.
This adjustment factor compensates for the increase in R2 that results solely from
increasing the number of independent variables.
Adjusted R2 is provided in the regression output.
It is particularly important to look at Adjusted R2, rather than R2, when comparing
regression models with different numbers of independent variables.
multicollinearity - CORRECT ANSWER-Multicollinearity occurs when there is a strong
linear relationship among two or more of the independent variables.
