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Instructions: After the student calculates the answers to this
homework he/she must submit the answers by placing them in
the Assignment # _ Submittal Link in Bb by midnight of the
date shown in the Course Roadmap and Syllabus. The Instructor
does not allow late submissions therefore a score of zero (0)
will be recorded for the assignment if submitted after midnight
Eastern Time of the due date.
Solution
s for the assignment will be released in Bb the morning after the
due date for access by students. Total points for the assignment
is 140. Note: There is no partial credit given; either the answer
is correct or incorrect.
Scenario: Ajax Manufacturing is an electronic test equipment
manufacturing firm that markets a certain piece of specialty test
equipment.
Ajax has several competitors who currently market similar
pieces of equipment.
While customers have repeatedly indicated they prefer Ajax’s
test equipment, they have historically proven to be unwilling to
wait for Ajax to manufacture this certain piece of equipment on
demand and will purchase their test equipment from Ajax’s
competitors in the event Ajax does not have the equipment
available in inventory for immediate delivery.
Thus, the key to Ajax successfully maintaining market share for
this particular piece of equipment has been to have it available
in stock for immediate delivery.
Unfortunately, it is a rather expensive piece of equipment to
maintain in inventory.
Period
Actual Number of Sold Units
Period
Actual Number of Sold Units
1
33
16
38
2
36
17
37
3
32
18
37
4
35
19
37
5
33
20
35
6
34
21
37
7
34
22
34
8
38
23
35
9
37
24
34
10
36
25
36
11
38
26
32
12
36
27
35
13
37
28
33
14
39
29
38
15
35
30
37
31
? Forecast ?
Thus, the president of Ajax Manufacturing is very interested in
accurately forecasting market demand in order to ensure he has
adequate inventory available to meet customer demand without
incurring undue inventory costs.
His sales department has provided historical data (in the table
above) regarding market demand for this certain piece of
specialty electronics test equipment for the past 30 months.
Instructions for Homework Assignment: Use the provided Excel
file to construct a spreadsheet for each of the four models
(Models 1-4) then answer Questions 26 - 28 based upon your
calculations.
Model 1: Answer the following questions.
Question 1. Calculate the projected demand for the test
equipment for the time periods 4 - 31 based upon a 3-month
moving average forecast model. What is the projected demand
for period 31? (5 points)
Question 2. Calculate the mean absolute deviation (MAD) for
the 3-month moving average forecast for each of the time
periods 4 through 30 and for the model. (5 points)
Question 3. Calculate the mean squared error (MSE) for the 3-
month moving average forecast for time periods 4 through 30
and for the model. (5 points)
Question 4. Calculate the mean absolute percent error (MAPE)
for the 3-month moving average forecast for time periods 4
through 30 and for the model. (5 points)
Question 5. Calculate the Standard Error for the model. (5
points)
Question 6. Calculate the Bias for the model. (5 points)
Model 2: Answer the following questions.
Question 7: Calculate the projected demand for the test
equipment for the time periods 4 - 31 based upon a 3-month
moving average forecast model for which the weighting factor
for actual demand one month ago is 3, the weighting factor for
actual demand two months ago is 2, and the weighting factor for
actual demand three months ago is 1. What is the projected
demand for period 31? (5 points)
Question 8: Calculate the mean absolute deviation (MAD) for
the 3-month weighted moving average forecast for each of the
time periods 4 through 30 and for the model. (5 points)
Question 9: Calculate the mean squared error (MSE) for the 3-
month weighted moving average forecast for time periods 4
through 30 and for the model. (5 points)
Question 10: Calculate the mean absolute percent error (MAPE)
for the 3-month weighted moving average forecast for time
periods 4 through 30 and for the model. (5 points)
Question 11: Calculate the Standard Error for the model. (5
points)
Question 12: Calculate the Bias for the model. (5 points)
Model 3: Answer the following questions.
Question 13: Calculate the projected demand for the test
equipment for the time periods 1 - 31 based upon using an
exponential smoothing forecast model for which alpha = 0.25.
Assume the Forecast is equal to the Demand for period 1. What
is the projected demand for period 31? (5 points)
Question 14: Calculate the mean absolute deviation (MAD) for
the exponential smoothing forecast for each of the time periods
1 through 30 and for the model. (5 points)
Question 15: Calculate the mean squared error (MSE) for the
exponential smoothing forecast for time periods 1 through 30
and for the model. (5 points)
Question 16: Calculate the mean absolute percent error (MAPE)
for the exponential smoothing forecast for time periods 1
through 30 and for the model. (5 points)
Question 17: Calculate the Standard Error for the model. (5
points)
Question 18: Calculate the Bias for the model. (5 points)
Model 4: Answer the following questions.
Question 19: Calculate the projected demand for the test
equipment for the time periods 1 - 31 based upon using a
Regression forecast model. What is the projected demand for
period 31? (5 points)
Question 20: Calculate the mean absolute deviation (MAD) for
the Regression forecast for each of the time periods 1 through
30 and for the model. (5 points)
Question 21: Calculate the mean squared error (MSE) for the
Regression forecast for time periods 1 through 30 and for the
model. (5 points)
Question 22: Calculate the mean absolute percent error (MAPE)
for the Regression forecast for time periods 1 through 30 and
for the model. (5 points)
Question 23: Calculate the Standard Error for the model. (5
points)
Question 24: Calculate the Bias for the model. (5 points)
Question 25: Discuss the correlation between the two variables
and is the relationship significant at the 95% level of
confidence? (5 points)
Question 26: Based upon using mean absolute deviation (MAD)
as a measure of forecast accuracy, which of the preceding
forecast models provides the greatest degree of forecasting
accuracy, and which of the preceding forecast models provides
the least degree of forecasting accuracy? (5 points)
Question 27: Based upon using Bias as a measure of forecast
accuracy, which of the preceding forecast models provides the
greatest degree of forecasting accuracy, and which of the
preceding forecast models provides the least degree of
forecasting accuracy? (5 points)
Question 28: Based upon using the Standard Error as a measure
of forecast accuracy, which of the preceding forecast models
provides the greatest degree of forecasting accuracy, and which
of the preceding forecast models provides the least degree of
forecasting accuracy? (5 points)
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Instructions After the student calculates the answers to this hom.docx

  • 1. Instructions: After the student calculates the answers to this homework he/she must submit the answers by placing them in the Assignment # _ Submittal Link in Bb by midnight of the date shown in the Course Roadmap and Syllabus. The Instructor does not allow late submissions therefore a score of zero (0) will be recorded for the assignment if submitted after midnight Eastern Time of the due date. Solution s for the assignment will be released in Bb the morning after the due date for access by students. Total points for the assignment is 140. Note: There is no partial credit given; either the answer is correct or incorrect. Scenario: Ajax Manufacturing is an electronic test equipment manufacturing firm that markets a certain piece of specialty test equipment. Ajax has several competitors who currently market similar pieces of equipment. While customers have repeatedly indicated they prefer Ajax’s test equipment, they have historically proven to be unwilling to wait for Ajax to manufacture this certain piece of equipment on
  • 2. demand and will purchase their test equipment from Ajax’s competitors in the event Ajax does not have the equipment available in inventory for immediate delivery. Thus, the key to Ajax successfully maintaining market share for this particular piece of equipment has been to have it available in stock for immediate delivery. Unfortunately, it is a rather expensive piece of equipment to maintain in inventory. Period Actual Number of Sold Units Period Actual Number of Sold Units 1 33
  • 8. Thus, the president of Ajax Manufacturing is very interested in accurately forecasting market demand in order to ensure he has adequate inventory available to meet customer demand without incurring undue inventory costs. His sales department has provided historical data (in the table above) regarding market demand for this certain piece of specialty electronics test equipment for the past 30 months. Instructions for Homework Assignment: Use the provided Excel file to construct a spreadsheet for each of the four models (Models 1-4) then answer Questions 26 - 28 based upon your calculations. Model 1: Answer the following questions. Question 1. Calculate the projected demand for the test equipment for the time periods 4 - 31 based upon a 3-month moving average forecast model. What is the projected demand for period 31? (5 points)
  • 9. Question 2. Calculate the mean absolute deviation (MAD) for the 3-month moving average forecast for each of the time periods 4 through 30 and for the model. (5 points) Question 3. Calculate the mean squared error (MSE) for the 3- month moving average forecast for time periods 4 through 30 and for the model. (5 points) Question 4. Calculate the mean absolute percent error (MAPE) for the 3-month moving average forecast for time periods 4 through 30 and for the model. (5 points) Question 5. Calculate the Standard Error for the model. (5 points) Question 6. Calculate the Bias for the model. (5 points) Model 2: Answer the following questions. Question 7: Calculate the projected demand for the test equipment for the time periods 4 - 31 based upon a 3-month moving average forecast model for which the weighting factor for actual demand one month ago is 3, the weighting factor for actual demand two months ago is 2, and the weighting factor for
  • 10. actual demand three months ago is 1. What is the projected demand for period 31? (5 points) Question 8: Calculate the mean absolute deviation (MAD) for the 3-month weighted moving average forecast for each of the time periods 4 through 30 and for the model. (5 points) Question 9: Calculate the mean squared error (MSE) for the 3- month weighted moving average forecast for time periods 4 through 30 and for the model. (5 points) Question 10: Calculate the mean absolute percent error (MAPE) for the 3-month weighted moving average forecast for time periods 4 through 30 and for the model. (5 points) Question 11: Calculate the Standard Error for the model. (5 points) Question 12: Calculate the Bias for the model. (5 points) Model 3: Answer the following questions. Question 13: Calculate the projected demand for the test equipment for the time periods 1 - 31 based upon using an
  • 11. exponential smoothing forecast model for which alpha = 0.25. Assume the Forecast is equal to the Demand for period 1. What is the projected demand for period 31? (5 points) Question 14: Calculate the mean absolute deviation (MAD) for the exponential smoothing forecast for each of the time periods 1 through 30 and for the model. (5 points) Question 15: Calculate the mean squared error (MSE) for the exponential smoothing forecast for time periods 1 through 30 and for the model. (5 points) Question 16: Calculate the mean absolute percent error (MAPE) for the exponential smoothing forecast for time periods 1 through 30 and for the model. (5 points) Question 17: Calculate the Standard Error for the model. (5 points) Question 18: Calculate the Bias for the model. (5 points) Model 4: Answer the following questions. Question 19: Calculate the projected demand for the test
  • 12. equipment for the time periods 1 - 31 based upon using a Regression forecast model. What is the projected demand for period 31? (5 points) Question 20: Calculate the mean absolute deviation (MAD) for the Regression forecast for each of the time periods 1 through 30 and for the model. (5 points) Question 21: Calculate the mean squared error (MSE) for the Regression forecast for time periods 1 through 30 and for the model. (5 points) Question 22: Calculate the mean absolute percent error (MAPE) for the Regression forecast for time periods 1 through 30 and for the model. (5 points) Question 23: Calculate the Standard Error for the model. (5 points) Question 24: Calculate the Bias for the model. (5 points) Question 25: Discuss the correlation between the two variables and is the relationship significant at the 95% level of confidence? (5 points)
  • 13. Question 26: Based upon using mean absolute deviation (MAD) as a measure of forecast accuracy, which of the preceding forecast models provides the greatest degree of forecasting accuracy, and which of the preceding forecast models provides the least degree of forecasting accuracy? (5 points) Question 27: Based upon using Bias as a measure of forecast accuracy, which of the preceding forecast models provides the greatest degree of forecasting accuracy, and which of the preceding forecast models provides the least degree of forecasting accuracy? (5 points) Question 28: Based upon using the Standard Error as a measure of forecast accuracy, which of the preceding forecast models provides the greatest degree of forecasting accuracy, and which of the preceding forecast models provides the least degree of forecasting accuracy? (5 points)