Quantitative Assignment
PRODUCTION MANAGEMENT
QUANTITATIVE
STUDENT’S NAME---------------------------------------------
NOTE: YOU MUST SHOW ALL YOUR CALCULATIONS WITH APPROPRIATE FORMULAS. ALL YOUR CALCULATION PROCESSES MUST BE DONE IN ORDER OR IN STEPS, AS POINTS ARE ASSIGNED ACCORDING TO THE STEPS OF CALCULATIONS TO THE FINAL ANSWER.
1. The transportation time and distance it take to deliver parts to customers are listed in the table 1. below:
TABLE #1.
|
|
Customer |
Rail Distance to Destination X |
Transportation time (days) Y |
|
|
|
|
1 |
Muller Auto Supply
|
210 |
5 |
|
|
|
|
2 |
Taylor Ford
|
290 |
7 |
|
|
|
|
3 |
Auto Supply House
|
350 |
6 |
|
|
|
|
4 |
Parts ‘n Spares
|
480 |
11 |
|
|
|
|
5 |
Jones & Sons
|
490 |
8 |
|
|
|
|
6 |
A. Housman
|
730 |
11 |
|
|
|
|
7 |
Des Moines Parts
|
780 |
12 |
|
|
|
|
8 |
Pete’s Parts
|
850 |
8 |
|
|
|
|
9 |
Smith Dodge
|
920 |
15 |
|
|
|
|
10 |
Gulf Distributors
|
1,010 |
12 |
|
|
|
|
|
|
|
|
|
|
|
a. Use the data above to estimate the linear trend forecast using the simple linear regression to calculate the trend line to predict the transportation time (Ŷ) for a customer living 490 miles away. (HINT): How many days it will take to deliver parts to a customer 490 miles away.
b. Compute the standard error of the estimate?
c. Now estimate the total variability in Y when the knowledge of X is ignored without regression
d. What conclusion can you make from the two prediction estimates from your calculations.
2. TABLE #2.
|
Week (t) |
Time Series Value (Yt) |
Forecast |
Error |
Absolute Deviation |
Error Square |
Abs. % error |
|
1 |
17 |
|
|
|
|
|
|
2 |
21 |
|
|
|
|
|
|
3 |
19 |
|
|
|
|
|
|
4 |
23 |
|
|
|
|
|
|
5 |
18 |
|
|
|
|
|
|
6 |
16 |
|
|
|
|
|
|
7 |
20 |
|
|
|
|
|
|
8 |
18 |
|
|
|
|
|
|
9 |
22 |
|
|
|
|
|
|
10 |
20 |
|
|
|
|
|
|
11 |
15 |
|
|
|
|
|
|
12 |
22 |
|
|
|
|
|
|
|
|
|
|
|
|
|
a. Use table #2 above to calculate the Mean Square Error calculation for the exponential smoothing forecast of gasoline sales with smoothing constant .2
NOTE: Show your answers on the table.
b. Based on the table you constructed above, calculate the Mean Absolute Deviation (MAD)
c. Based on the table you constructed above, calculate the Mean Square Error (MSE)
d. Based on the table you constructed above, calculate the Mean Absolute Percent Error (MAPE).
TABLE 3.
3.
Kenny’s Unique Trapping is comparing the accuracy of two methods that she has used to forecast monthly sales of her popular hair weaves. Forecast of monthly sales from January through May for methods ‘A’ and ‘B’ are shown below against the actual sales. Which method provided better forecast accuracy” (Please show all calculations before explaining your answer based on your calculations)
|
METHOD A METHOD B |
||||||||||
|
Month
|
Sales |
forecast |
|
|
|
|
Forecast |
|
|
|
|
Jan
|
40 |
42 |
|
|
|
|
44 |
|
|
|
|
Feb
|
28 |
29 |
|
|
|
|
31 |
|
|
|
|
Mar
|
41 |
39 |
|
|
|
|
38 |
|
|
|
|
Apr
|
41 |
38 |
|
|
|
|
42 |
|
|
|
|
May
|
39 |
41 |
|
|
|
|
40 |
|
|
|
|
|
|
|
|
|
|
|
|
|
|
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