BUSINESS ANALYTICS EXAM 2024-2025
WITH LATEST QUESTIONS AND
CORRECT ANSWERS ALREADY GRADED
A+
What is the difference between analyzing residual plots for single variable regression models and
analyzing residual plots for multiple regression models - ANS-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.
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? - ANS-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.
R-squared vs adjusted R-squared - ANS-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 - ANS-Multicollinearity occurs when there is a strong linear relationship among two or
more of the independent variables.
What does R-square indicate? - ANS-R-square indicates what percentage of the variability in the
dependent variable is explained by the regression line
multicollinearity - ANS-Multicollinearity occurs when two or more independent variables are highly
correlated
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? - ANS-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)
WITH LATEST QUESTIONS AND
CORRECT ANSWERS ALREADY GRADED
A+
What is the difference between analyzing residual plots for single variable regression models and
analyzing residual plots for multiple regression models - ANS-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.
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? - ANS-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.
R-squared vs adjusted R-squared - ANS-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 - ANS-Multicollinearity occurs when there is a strong linear relationship among two or
more of the independent variables.
What does R-square indicate? - ANS-R-square indicates what percentage of the variability in the
dependent variable is explained by the regression line
multicollinearity - ANS-Multicollinearity occurs when two or more independent variables are highly
correlated
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? - ANS-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)
