Unit 6 Assignment (Read Carefully)
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Unit 6: Assignment
In this Assignment, you will be assessed based on the following outcomes:
GB513-4: Evaluate real-world situations and present solutions using statistical methods.
PC-6.1: Incorporate data, inferences, and reasoning to solve problems.
This Assignment has two parts. Part 1 has questions about forecasting. You will submit your
answers using the Unit 6 Assignment template located in Course Documents for Part 1.
Part 2 requires you to analyze a case. For this, you will prepare a PowerPoint presentation to
present your findings. See below under “Part 2-Case Analysis” for more details.
Part 1 – Forecasting
Answer the following three questions using the template provided.
Question 1
A marketing manager is forecasting the sales of cars per week. Determine the error for each of the
following forecasts. Then, calculate MAD and MSE.
Period Value Forecast Error
1 202 — —
2 191 202
3 173 192
4 169 181
5 171 174
6 175 172
7 182 174
8 196 179
9 204 189
10 219 198
11 227 211
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Question 2
The U.S. Census Bureau publishes data on factory orders for all manufacturing, durable goods,
and nondurable goods industries. Shown below are factory orders in the United States over a 13 -
year period ($ billion).
First, use the data to develop forecasts for years 6 through 13 using a 5-year moving average.
Then, use the data to develop forecasts for years 6 through 13 using a 5-year weighted moving
average. Weight the most recent year by 6, the previous year by 4, the year before that by 2,
and the other years by 1.
Answer the following questions:
a) What is the forecast for year 13 based on the 5-year moving average?
b) What is the forecast for year 13 based on the 5-year weighted moving average?
c) What is the MAD for the moving average forecast?
d) What is the MAD for the weighted moving average forecast?
e) Which forecasting model is better?
Year Factory
orders
1 2,512.70
2 2,739.20
3 2,874.90
4 2,934.10
5 2,865.70
6 2,978.50
7 3,092.40
8 3,052.60
9 3,145.20
10 3,114.10
11 3,257.40
12 3,654.00
13
Question 3
The “Economic Report to the President of the United States” included data on the amounts
of manufacturers’ new and unfilled orders in millions of dollars. Shown here are the figures
for new orders over a 21-year period.
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Use the charting tool in Excel to develop a regression model to fit the trend effects for the data.
Use a linear model and then try a polynomial (order 2) model. Make sure the charts show the line
formula and the r-squared value. Include both charts in your report. Then, answer the following
question:
● How well does either model fit the data? Which model should be used for forecasting?
Explain using the relevant metrics.
Year Total Number
of New Orders
1 55,022
2 55,921
3 64,182
4 76,003
5 87,327
6 85,139
7 99,513
8 115,109
9 116,251
10 121,547
11 123,321
12 141,200
13 162,140
14 168,420
15 171,250
16 176,355
17 195,204
18 209,389
19 237,025
20 272,544
21 293,475
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Part 2 – Case Analysis
To answer Part 2, you will prepare a PowerPoint presentation to present your findings. Make sure
you also submit the Excel file to show your work for Part 2. You will receive a reduction in points
if you fail to include the Excel file showing your work for Part 2.
Place all calculations for each of the questions on a separate worksheet. Then, using the
results of your work from Excel, prepare PowerPoint slides to answer the questions in a
presentation format. All relevant content should be on the slides; do not use the notes
section or leave information in the Excel file. The executives reviewing the presentation should
not need to switch to another document to see the required information.
The data you need is provided to you in the Unit 6 Excel file in Course Documents. Make
sure to use that file. Do not type anything in manually or download anything from the
Internet.
You will be analyzing the “Colonial Broadcasting” case in the coursepack. Begin by reading
the description in the case. Then, answer the questions listed below, NOT the questions
listed in the case. Ignore everything in the case after the end of page 4.
The executives at CBC want to see how they are doing in ratings against the other networks and
how the ratings will continue to change in the upcoming months. They also want to know if hiring
stars makes a difference and the impact of fact-based programming compared to hiring stars.
Remember that your audience is the management of CBC. Therefore, make sure your
presentation is professional and provides sufficient explanation.
1. Answer the following questions:
a. What is the average rating for all CBC movies? How about ABN movies and
BBS movies?
b. Include a table that shows the average and the other descriptive statistics (using
the data analysis tool pack in Excel) for the ratings of the three networks (one
column for each network). Explain what you learn from each of the metrics in the
table.
c. Comment on which network is doing best.
2. Create a line graph of the monthly average ratings for CBC for the year. Note that there
are multiple ratings data for the months; you will need to calculate an average for each
month first, and then plot the averages. After you create the graph, fit a linear trend line,
displaying the formula and the r-squared. Explain to the executives if you can use this
time series data to forecast the ratings of upcoming months. How accurate can you expect
this forecast to be?
3. Should the CBC hire stars for their movies? To answer this question, run a hypothesis test
to see if there is a significant difference between the ratings of movies with stars versus
movies without stars. Use the data for CBC movies only. Use 95% confidence.
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Answer the following:
a. What are the null and alternative hypotheses (state in full sentences)?
b. Run the test using Excel and include the output table. Use a t-test assuming
equal variances.
c. What is your recommendation to the executives? Justify your answer referring to
the relevant figures.
4. Run a multiple regression where the dependent variable is ratings and the independent
variables are star and fact. Use data from CBC only. CBC Management has several
questions:
a. Which has more impact on a movie’s rating: Being fact-based or having one star?
How much does each of these factors change the ratings?
b. How well does this regression analysis explain the ratings? Justify your
answers referring to the relevant figures.
c. Are either, both, or neither of the independent variables significantly related to
the ratings at 95% confidence? Justify your answers referring to the relevant
figures.
Directions for Submitting your Assignment:
Be sure to complete the Unit 6 Assignment template. Submit your Assignment to the Unit 6
Assignment Dropbox.
Unit 6 Assignment
Content
Points
Possible
Points
Earned
Part 1 - Forecasting
Question 1
Provided the MAD.
5
Question 1
Provided the MSE.
5
Question 2a
Correct forecast for year 13 using a 5-year moving average.
5
Question 2b
Correct forecast for year 13 using a 5-year weighted moving
average.
5
Question 2c
Correct MAD for moving average forecast.
5
Question 2d
Correct MAD for weighted moving average forecast.
5
Question 2e
Recommended the better model with justification.
5
Question 3
Used Excel charting to fit a linear trendline, including the formula
and r-squared.
5
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Question 3
Used Excel charting to fit a polynomial trendline, including the
formula and r-squared.
5
Question 3
Recommended the better model with justification.
5
Part 2 – Case Analysis
Question 1
Correct average rating for all three networks. 10
Question 1
Correct table showing the average and other descriptive statistics
for the ratings of the three networks, using one column for each
network.
10
Question 1
Appropriate explanation and analysis of what is learned from each
of the metrics in the descriptive statistics table.
20
Question 2
Correct line graph using the calculated average monthly ratings of
CBC for the year, showing r-squared and the formula.
20
Question 2
Summary to executives regarding whether the linear forecast can
be used to project ratings, including an assessment of how
accurate the forecast can be expected to be.
20
Question 3
Correct null and alternative hypotheses stated in full sentences. 20
Question 3
Accurate hypothesis test results. 20
Question 3
Correct recommendation and justification for whether CBC should
hire stars.
20
Question 4
Appropriate explanation on what has more impact on a movie’s
rating: Whether the movie includes a star or whether it is fact-
based.
20
Question 4
Explanation of how well this regression analysis explains the
ratings.
20
Question 4
Accurate identification and justification of which variables are
significantly related to ratings.
20
PowerPoint is formatted appropriately and communicated clearly. 50
Total 300