MKT 317 EXAM QUESTIONS WITH
COMPLETE ANSWERS
For this question, you will need to use R and a built-in data set named
longley. Since this is a built-in data set, you do not need to download or
import the data into R. This is the data set that we used in the Module 4
Lab Part 2 (however this model is different from what we created in that
lab).
Use the data set named longley to create a linear model where
The dependent variable (y-variable) is Employed
The independent variable (x-variable) is Population
When creating the model
Predicted Employed = b0 + b1(Population)
For this model, the slope, b1, equals ________ . - ANSWER 0.485
Suppose Dr. Bronlyn creates the following model. In the equation below, ln
represents the natural log.
ln(Y) = ln(60) + 2(X)
What describes the relationship between X and the predicted (average)
value of Y? - ANSWER An absolute change in X corresponds to a
percentage change in the predicted value of Y.
Suppose Dr. Bronlyn has a data set named MKT317_PracticeData
She uses R and Tableau to create the linear regression model with output
given below:
Equation of model: Predicted Y = 41 + 11.5(X)
p-value for the intercept: 0.0409
p-value for the slope: 0.0069
R-squared for the model: 0.8549
,From the output above, Dr. Bronlyn would conclude that ________ % of the
variability of Y can be explained by this model. - ANSWER 85
Suppose Dr. Bronlyn has a large data set named MKT317_PracticeData
(this is a fictional data set that you do not need to import into R).
This data set has five variables: Y, X1, X2, X3, and X4.
We have the following information:
The correlation coefficient for Y and X1 equals -0.22
The correlation coefficient for Y and X2 equals 0.54
The correlation coefficient for Y and X3 equals -0.87
The correlation coefficient for Y and X4 equals 0.01
Among the variables X1, X2, X3, and X4 in the MKT317_PracticeData set,
which variable has the strongest correlation with Y? - ANSWER X3
Suppose Dr. Bronlyn has a very large data set about a retail organization.
This data set is very large: it has several thousand rows of data, and has
approximately 30 independent variables.
Her goal is to create a simple linear regression model that predicts the
Profit using the independent variable that is the most strongly correlated
with Profit.
What method should Dr. Bronlyn use? - ANSWER Create a correlogram
and create a model using the independent variable that is associated with
the biggest dot in the row or column labeled "Y."
Suppose Dr. Bronlyn has a large data set, and she uses it to create the
model below.
From that data set, she uses variables Revenue and Temperature to create
the linear model below, where the Revenue is measured in thousand
dollars and Temperature is measured in degrees Fahrenheit.
Dr. Bronlyn uses R to obtain the information below:
Equation of the model: Predicted Revenue (thousand dollars) = 150 +
7(Temperature).
The p-value for the slope equals 0.0015
The p-value for the slope equals 0.0029
The R-squared for the model equals 0.7109
When the temperature equals 85 degrees Fahrenheit, the predicted
revenue equals _______ thousand dollars. - ANSWER 745
What is a correlogram? - ANSWER A visual way to represent the strength
and direction of correlations for several pairs of variables.
, Suppose we have a multiple linear regression model that is not reduced.
What does this mean? - ANSWER There is at least one X-variable in the
model that can be removed from the model without significantly reducing
the accuracy.
Suppose a large data set includes information about the weights
(measured in carats) and prices (measured in US dollars) of recent
diamond sales.
The data produce the linear model below, and the R-squared value for this
model is 0.92
Predicted Price = -2,250 + 7,800(weight)
What can we conclude from the R-squared value of 0.92? - ANSWER 92%
of the variability in prices of recent diamond sales can be explained by the
diamonds' weights.
Suppose Dr. Bronlyn has data set with variables Sales and Discount. The
data is saved in a data set named MKT317ExampleData.
She can use Tableau to compute the trend line: Predicted Sales = 30 +
22*(Discount)
Suppose Dr. Bronlyn wants some additional statistical output, so she
decides to create the same model in R. What commands would she use? -
ANSWER lm(Sales ~ Discount, data=MKT317ExampleData)
Suppose Dr. Bronlyn has a data set named MKT317ExampleData
One of the variables in this data set is named "Revenue."
What R command did we learn in class that would tell us the average value
of Sales in the MKT317ExampleData data set? - ANSWER
summary(MKT317ExampleData)
Suppose Dr. Bronlyn has a large data set, which she uses to create the
model below.
From that data set, she uses variables Profit and Budget to create the
linear model below, where the units of Budget and Profit are in dollars.
Dr. Bronlyn uses R to obtain the information below:
Equation of the model: Predicted Profit = 20,000 + 2.1(Budget).
The p-value for the slope equals 0.0107
The p-value for the slope equals 0.0060
The R-squared for the model equals 0.7010
COMPLETE ANSWERS
For this question, you will need to use R and a built-in data set named
longley. Since this is a built-in data set, you do not need to download or
import the data into R. This is the data set that we used in the Module 4
Lab Part 2 (however this model is different from what we created in that
lab).
Use the data set named longley to create a linear model where
The dependent variable (y-variable) is Employed
The independent variable (x-variable) is Population
When creating the model
Predicted Employed = b0 + b1(Population)
For this model, the slope, b1, equals ________ . - ANSWER 0.485
Suppose Dr. Bronlyn creates the following model. In the equation below, ln
represents the natural log.
ln(Y) = ln(60) + 2(X)
What describes the relationship between X and the predicted (average)
value of Y? - ANSWER An absolute change in X corresponds to a
percentage change in the predicted value of Y.
Suppose Dr. Bronlyn has a data set named MKT317_PracticeData
She uses R and Tableau to create the linear regression model with output
given below:
Equation of model: Predicted Y = 41 + 11.5(X)
p-value for the intercept: 0.0409
p-value for the slope: 0.0069
R-squared for the model: 0.8549
,From the output above, Dr. Bronlyn would conclude that ________ % of the
variability of Y can be explained by this model. - ANSWER 85
Suppose Dr. Bronlyn has a large data set named MKT317_PracticeData
(this is a fictional data set that you do not need to import into R).
This data set has five variables: Y, X1, X2, X3, and X4.
We have the following information:
The correlation coefficient for Y and X1 equals -0.22
The correlation coefficient for Y and X2 equals 0.54
The correlation coefficient for Y and X3 equals -0.87
The correlation coefficient for Y and X4 equals 0.01
Among the variables X1, X2, X3, and X4 in the MKT317_PracticeData set,
which variable has the strongest correlation with Y? - ANSWER X3
Suppose Dr. Bronlyn has a very large data set about a retail organization.
This data set is very large: it has several thousand rows of data, and has
approximately 30 independent variables.
Her goal is to create a simple linear regression model that predicts the
Profit using the independent variable that is the most strongly correlated
with Profit.
What method should Dr. Bronlyn use? - ANSWER Create a correlogram
and create a model using the independent variable that is associated with
the biggest dot in the row or column labeled "Y."
Suppose Dr. Bronlyn has a large data set, and she uses it to create the
model below.
From that data set, she uses variables Revenue and Temperature to create
the linear model below, where the Revenue is measured in thousand
dollars and Temperature is measured in degrees Fahrenheit.
Dr. Bronlyn uses R to obtain the information below:
Equation of the model: Predicted Revenue (thousand dollars) = 150 +
7(Temperature).
The p-value for the slope equals 0.0015
The p-value for the slope equals 0.0029
The R-squared for the model equals 0.7109
When the temperature equals 85 degrees Fahrenheit, the predicted
revenue equals _______ thousand dollars. - ANSWER 745
What is a correlogram? - ANSWER A visual way to represent the strength
and direction of correlations for several pairs of variables.
, Suppose we have a multiple linear regression model that is not reduced.
What does this mean? - ANSWER There is at least one X-variable in the
model that can be removed from the model without significantly reducing
the accuracy.
Suppose a large data set includes information about the weights
(measured in carats) and prices (measured in US dollars) of recent
diamond sales.
The data produce the linear model below, and the R-squared value for this
model is 0.92
Predicted Price = -2,250 + 7,800(weight)
What can we conclude from the R-squared value of 0.92? - ANSWER 92%
of the variability in prices of recent diamond sales can be explained by the
diamonds' weights.
Suppose Dr. Bronlyn has data set with variables Sales and Discount. The
data is saved in a data set named MKT317ExampleData.
She can use Tableau to compute the trend line: Predicted Sales = 30 +
22*(Discount)
Suppose Dr. Bronlyn wants some additional statistical output, so she
decides to create the same model in R. What commands would she use? -
ANSWER lm(Sales ~ Discount, data=MKT317ExampleData)
Suppose Dr. Bronlyn has a data set named MKT317ExampleData
One of the variables in this data set is named "Revenue."
What R command did we learn in class that would tell us the average value
of Sales in the MKT317ExampleData data set? - ANSWER
summary(MKT317ExampleData)
Suppose Dr. Bronlyn has a large data set, which she uses to create the
model below.
From that data set, she uses variables Profit and Budget to create the
linear model below, where the units of Budget and Profit are in dollars.
Dr. Bronlyn uses R to obtain the information below:
Equation of the model: Predicted Profit = 20,000 + 2.1(Budget).
The p-value for the slope equals 0.0107
The p-value for the slope equals 0.0060
The R-squared for the model equals 0.7010
