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Marketing Analytics Spring 2020 Final Exam
MKAN1-UC 5103 Marketing Analytics Spring 2020 Final Exam
Instructions (total 3 points):
• Develop the SAS syntax for each question in both Part I and Part II below and
save all syntax in ONE SAS file called "YourLastName_MA_Final_Exam"
You will need to save your Final Exam as a PDF File and submit that file. To save
as PDF, you can use the menu for Print and instead of a printer you will select
“Save as PDF” (cmd and P, on a Mac then select from bottom left, or Ctrl and P
on Windows then Destination “Save as PDF”).
Please inspect your PDF file before you submit it to ensure that no detail is cut
off (this will reduce your points). If any detail does not display on the PDF, you
may need to resize and add extra lines accordingly.
• Submit that file under this “Final Exam” Assignment as your answer to Final Exam
• Start your SAS file with this header by using SAS comments syntax:
o Course Name - Semester Year
o Your name
o Final Exam - date you complete the assignment
• Start your answer to each question below with the Question # by using SAS
comments syntax
• Keep your syntax in a clear format
• Please copy and paste the syntax generated into your SAS file even if you use
point-and-click methods/tasks
Questions (total 107 points):
Part I – sales csv dataset
1. (3 points) (1) Import “sales.csv” file into a SAS data set named “sales” in one of
your libraries. (2) Use proper syntax statements to rename the name of the
“QUANTITYORDERED” column in the sales data set into “quantity” and the
“PRICEEACH” column into “price”. (3) Use proper syntax statements to create a
new column in the data set called “revenue” where revenue = quantity * price.
2. (6 points) Based on Question 1, (1) create a Bar Chart showing the total number
of revenue the store earned by year id. (2) Use SAS comments syntax to describe
the information that you see from RESULTS (explain the chart).
3. (6 points) Based on Question 1, (1) create a Line Chart showing the average
quantity the store sold by month of the year. (2) Use SAS comments syntax to
describe the information that you see from RESULTS (explain the chart).
4. (6 points) Based on Question 1, (1) create a Pie Chart showing the total quantity
by deal size. (2) Use SAS comments syntax to describe the information that you
see from RESULTS (explain the chart).
2
Marketing Analytics Spring 2020 Final Exam
5. (6 points) Based on Question 1, (1) create a Mosaic Plot where y-axis is year id
and x-axis is product line. (2) Use SAS comments syntax to describe the
information that you see from RESULTS (explain the chart).
6. (6 points) Based on Question 1, (1) Create a Box Plot showing the revenue the
store earned by product line. Also, in Settings APPEARANCE, add a proper title
for the chart. (2) Use SAS comments syntax to describe the information that you
see from RESULTS (explain the plot).
7. (9 points) Based on Question 1, (1) use point and click Distribution Analysis Task
under Statistics to analyze the distribution of the “revenue” variable (make sure
in OPTIONS, check Histogram and goodness-of-fit tests, and Normal quantilequantile
plot). (2) Use SAS comments syntax to answer the questions below:
a. From the histogram, what you can conclude?
b. From goodness-of-fit tests, what is the null hypothesis? Based on the pvalue,
do we reject the null hypothesis? Then, what can we conclude
from the test?
c. What does Q-Q plot tell us?
8. (9 points) Based on Question 1, (1) use point and click One-sample T Test Task
under Statistics to test if the mean of the revenue variable is equal to 3,000. (2)
Use SAS comments syntax to answer the questions below:
a. What is the assumption of one-sample t-test? Does the target variable
“revenue” meet the assumption? How do you know?
b. What is the null hypothesis for this t-test? Do we reject the null
hypothesis? Why or why not? What will you conclude?
9. (10 points) Based on Question 1, (1) use point and click One-Way ANOVA Task
under Linear Models to test if the means of the revenue in different product line
groups are the same or not. (2) Use SAS comments syntax to answer the
questions below:
a. What are the two assumptions of One-Way ANOVA? Choose one
assumption to answer: Does the target variable “revenue” meet the
assumption you choose? How do you know?
b. What is the null hypothesis for this One-Way ANOVA test? Do we reject
the null hypothesis? Why or why not? What will you conclude?
c. List three specific pairs of product line groups where the mean revenues
are significantly different (significance level = 0.05)? How do you know
they have significant different means in revenue?
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Marketing Analytics Spring 2020 Final Exam
Part II – skincancer csv dataset
Dataset Description
State State Name in US
Lat Latitude
Mort Skincancer mortality cases
Ocean If it is near Ocean or not -- Yes 1; No 0
Long Longitude
1. (2 points) Import “skincancer.csv” file into a SAS data set named “skincancer” in
one of your libraries.
2. (6 points) Based on Question 1, (1) create a Scatter Plot showing the relationship
between latitude and skincancer mortality cases. (2) Use SAS comments syntax
to describe the information that you see from RESULTS (explain the plot).
3. (9 points) Based on Question 1, (1) use point and click Correlation Analysis Task
under Statistics to explore the linear relationship between mortality, latitude and
longitude (Make sure to display p-values under OPTIONS-Statistics). (2) Use SAS
comments syntax to answer the questions below:
a. What are the relationships between each pair of the three variables?
How do you know?
b. Which correlation amongst the three variables is/are significant? How do
you know?
4. (10 points) Based on Question 1, (1) use point and click Two-sample T Test Task
under Statistics to test if the means of the mortality cases near ocean and far
away from ocean are the same or not. (2) Use SAS comments syntax to answer
the questions below:
a. What are the two assumptions of Two-sample t-test? Does the target
variable meet both assumptions or not? How do you know?
b. What is the null hypothesis for this Two-sample t-test? Do we reject the
null hypothesis? Why or why not? What will you conclude?
c. Is there any limitation in this two-sample t-test? If yes, please explain. If
no, why not?
5. (10 points) Based on Question 1, (1) create a Linear Regression Model to predict
the mortality cases by using latitude and longitude variables. (2) Use SAS
comments syntax to answer the questions below:
a. Explain the meanings of different p-values in the results. What shall we
conclude about the different variables and the model?
b. What is the value of R Square? What does it mean?
4
Marketing Analytics Spring 2020 Final Exam
6. (9 points) Based on Question 1, (1) create a Linear Regression Model to predict
the mortality cases by using latitude and the interaction effect between ocean
and latitude. (2) Use SAS comments syntax to answer the questions below:
a. Explain the meanings of different p-values in the results. What shall we
conclude about the different variables and the model?
b. Is this model better than the model in Question 5 above? How do you
know?
Note:
• This is a 110-point Final Exam. You need to submit your answers by the due time,
answer satisfactorily all points in each question and follow these instructions
fully. Late submissions will receive automatic 0 points.
• This is an individual take-home Final Exam. Any teamwork found will receive
automatic 0 points.

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