Question

In: Math

Two independent methods of forecasting based on judgment and experience have been prepared each month for...

Two independent methods of forecasting based on judgment and experience have been prepared each month for the past 10 months. The forecasts and actual sales are as follows:

Month Sales Forecast 1 Forecast 2
1 845 815 820
2 835 835 825
3 795 820 825
4 820 830 795
5 795 785 780
6 835 785 771
7 805 810 785
8 850 780 785
9 840 805 830
10 805 815 825

     

a. Compute the MSE and MAD for each forecast. (Round your answers to 2 decimal places.)

MSE MAD
Forecast 1 ? ?
Forecast 2 ? ?

   

b. Compute MAPE for each forecast. (Round your intermediate calculations to 5 decimal places and final answers to 4 decimal places.)

MAPE F1 ? %
MAPE F2 ? %

c. Prepare a naive forecast for periods 2 through 11 using the given sales data. Compute each of the following; (1) MSE, (2) MAD, (3) tracking signal at month 10, and (4) 2s control limits. (Round your answers to 2 decimal places.)

MSE ?
MAD ?
Tracking signal ?
Control limits 0 ± ?

Solutions

Expert Solution

a. Compute the MSE and MAD for each forecast. (Round your answers to 2 decimal places.)

Month Sales Forecast 1 Forecast 2 Error(Seles - Forecast 1) Absolute Error Error(Seles - Forecast 2) Absolute Error
1 845 815 820 30 30 25 25
2 835 835 825 0 0 10 10
3 795 820 825 -25 25 -30 30
4 820 830 795 -10 10 25 25
5 795 785 780 10 10 15 15
6 835 785 771 50 50 64 64
7 805 810 785 -5 5 20 20
8 850 780 785 70 70 65 65
9 840 805 830 35 35 10 10
10 805 815 825 -10 10 -20 20
MAD F1 24.5 MAD F2 28.4
Month Sales Forecast 1 Forecast 2 Error(Seles - Forecast 1) Absolute Error Squared Absolute Error Error(Seles - Forecast 2) Absolute Error Squared Absolute Error
1 845 815 820 30 30 900 25 25 625
2 835 835 825 0 0 0 10 10 100
3 795 820 825 -25 25 625 -30 30 900
4 820 830 795 -10 10 100 25 25 625
5 795 785 780 10 10 100 15 15 225
6 835 785 771 50 50 2500 64 64 4096
7 805 810 785 -5 5 25 20 20 400
8 850 780 785 70 70 4900 65 65 4225
9 840 805 830 35 35 1225 10 10 100
10 805 815 825 -10 10 100 -20 20 400
MSE F1 1047.5 MSE F2 1169.6

where the total MSE and MAD is calculated by finding the average of the whole column.

So, we have:

MAD F1 24.5 MAD F2 28.4
MSE F1 1047.50 MSE F2 1169.60

b. Compute MAPE for each forecast. (Round your intermediate calculations to 5 decimal places and final answers to 4 decimal places.)

Month Sales Forecast 1 Forecast 2 Error(Seles - Forecast 1) Absolute Error MAPE = (Absolute Error/Sales)*100 Error(Seles - Forecast 2) Absolute Error MAPE = (Absolute Error/Sales)*100
1 845 815 820 30 30 3.55030 25 25 2.95858
2 835 835 825 0 0 0.00000 10 10 1.19760
3 795 820 825 -25 25 3.14465 -30 30 3.77358
4 820 830 795 -10 10 1.21951 25 25 3.04878
5 795 785 780 10 10 1.25786 15 15 1.88679
6 835 785 771 50 50 5.98802 64 64 7.66467
7 805 810 785 -5 5 0.62112 20 20 2.48447
8 850 780 785 70 70 8.23529 65 65 7.64706
9 840 805 830 35 35 4.16667 10 10 1.19048
10 805 815 825 -10 10 1.24224 -20 20 2.48447
MAPE F1 2.9426% MAPE F2 3.4336%

where the total MAPE is calculated by finding the average of the whole column.

So, we have:

MAPE F1 2.9426% MAPE F2 3.4336%

c. Prepare a naive forecast for periods 2 through 11 using the given sales data. Compute each of the following; (1) MSE, (2) MAD, (3) tracking signal at month 10, and (4) 2s control limits. (Round your answers to 2 decimal places.)

Month Sales Forecast Error (Sales - Forecast) Absolute Error Squared Error Absolute % Error (Absolute Error/Sales)*100
1 845
2 835 845 -10 10 100 1.197605
3 795 835 -40 40 1600 5.031447
4 820 795 25 25 625 3.04878
5 795 820 -25 25 625 3.144654
6 835 795 40 40 1600 4.790419
7 805 835 -30 30 900 3.726708
8 850 805 45 45 2025 5.294118
9 840 850 -10 10 100 1.190476
10 805 840 -35 35 1225 4.347826
Total 8225 31.77203
MAD 28.88889 MSE 977.7778

where the total MSE and MAD is calculated by finding the average of the whole column.

So, we have:

MAD 28.89 MSE 977.78
Month Sales Forecast Error (Sales - Forecast)
1 845
2 835 845 -10
3 795 835 -40
4 820 795 25
5 795 820 -25
6 835 795 40
7 805 835 -30
8 850 805 45
9 840 850 -10
10 805 840 -35
Total -40
Tracking signal at month 10 -1.38462

Tracking signal at month 10 = Total Error/MAD = -40/28.88889 = -1.38

Control limits = 0 ± 2*√(MSE) = 0 ± 2*√​​​​​​​(977.78) = 0 ± 2*31.27 = 0 ± 62.54

Control limits = 0 ± 62.54

milcah answered 1 year ago
Next > < Previous

Related Solutions

Two independent methods of forecasting based on judgment and experience have been prepared each month for...
Two independent methods of forecasting based on judgment and experience have been prepared each month for the past 10 months. The forecasts and actual sales are as follows: Month Sales Forecast 1 Forecast 2 1 771 774 772 2 790 789 791 3 794 792 792 4 776 776 775 5 772 773 772 6 770 771 772 7 761 761 765 8 774 778 778 9 792 792 794 10 794 798 797 a. Compute a tracking signal for...
Two independent methods of forecasting based on judgment and experience have been prepared each month for...
Two independent methods of forecasting based on judgment and experience have been prepared each month for the past 10 months. The forecasts and actual sales are as follows: Month Sales Forecast 1 Forecast 2 1 840 810 795 2 835 780 825 3 810 835 850 4 845 840 840 5 790 775 800 6 845 790 806 7 820 785 810 8 850 770 805 9 830 835 840 10 795 785 810       a. Compute the MSE and...
Two independent methods of forecasting based on judgment and experience have been prepared each month for...
Two independent methods of forecasting based on judgment and experience have been prepared each month for the past 10 months. The forecasts and actual sales are as follows: Month Sales Forecast 1 Forecast 2 1 830 790 760 2 845 800 795 3 795 805 820 4 825 815 830 5 770 780 795 6 835 790 796 7 785 765 800 8 835 785 835 9 805 800 810 10 855 820 795 c. Prepare a naive forecast for...
Two independent methods of forecasting based on judgment and experience have been prepared each month for...
Two independent methods of forecasting based on judgment and experience have been prepared each month for the past 10 months. The forecasts and actual sales are as follows: Month Sales Forecast 1 Forecast 2 1 845 815 820 2 835 835 825 3 795 820 825 4 820 830 795 5 795 785 780 6 835 785 771 7 805 810 785 8 850 780 785 9 840 805 830 10 805 815 825       a. Compute the MSE and...
Problem 3-22 Two independent methods of forecasting based on judgment and experience have been prepared each...
Problem 3-22 Two independent methods of forecasting based on judgment and experience have been prepared each month for the past 10 months. The forecasts and actual sales are as follows: Month Sales Forecast 1 Forecast 2 1 830 800 780 2 835 825 830 3 790 800 820 4 800 815 830 5 785 820 815 6 825 805 786 7 775 770 805 8 860 830 820 9 810 805 785 10 810 845 840       a. Compute the...
1.      Two independent forecasting methods have been used each week for the past 5 weeks. The...
1.      Two independent forecasting methods have been used each week for the past 5 weeks. The forecasts and actual sales are as follows. Week Actual Sales (number of units) Sales Forecasts (number of units) Method 1 Method 2 Five weeks ago 20 18 21 Four weeks ago 19 19 20 Three weeks ago 21 20 19 Two weeks ago 18 19 17 Last week 22 23 22 a.      Calculate the Mean Absolute Deviation (MAD) measures for forecasting methods 1 and...
Forecasting Exchange Rates Explain two of the methods for forecasting exchange rates and provide examples of...
Forecasting Exchange Rates Explain two of the methods for forecasting exchange rates and provide examples of how they might work.
Explain the role of forecasting, identifying different methods, and the strengths and weaknesses of each
Explain the role of forecasting, identifying different methods, and the strengths and weaknesses of each
Question 1 The simulation models that have been based on independent trials in which the results...
Question 1 The simulation models that have been based on independent trials in which the results for one trial do not affect what happens in subsequent trials are referred to as: static simulation models dynamic simulation models discrete-event simulation models continuous-event simulation models Question 2 In an inventory simulation model, the percentage of total demand that will be satisfied is referred to as: the service level the optimal order quantity customer satisfaction level the optimal inventory level Question 3 If...
For your analysis, you have been asked to compare methods based on a machine that cost...
For your analysis, you have been asked to compare methods based on a machine that cost $176,000. The estimated useful life is 10 years, and the estimated residual value is $33,440. The machine has an estimated useful life in productive output of 216,000 units. Actual output was 28,000 in year 1 and 24,000 in year 2. Required: 1. For years 1 and 2 only, prepare separate depreciation schedules assuming: (Do not round intermediate calculations and round your final answers to...
ADVERTISEMENT
Subjects
ADVERTISEMENT
Latest Questions
ADVERTISEMENT