i. Find three months weighted moving averages by assuming the weights 1 0.15 W = , 2 0.36W = and 3 0.49 W = . ii. Compute the mean forecast errors. iii. Compute the mean square error
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QUESTION THREE
(a)
The actual demand of a product for 6 months are summarized in Table below:
Actual Demand Values
Month ( ) t Demand ( ) tD
1 300
2 450
3 700
4 900
5 1200
6 1400
i.
Find three months weighted moving averages by assuming the weights 1 0.15 W = ,
2 0.36W = and 3 0.49 W = .
ii.
Compute the mean
iii.
Compute the mean square error
Step by step
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- Question 3: Jane is trying to forecast demand for her store, using moving average with n=2, Fill in the missing cells with correct values and find average error for first quarter and second quarter of year 2000 E Enroll- Year Quarter ment Forecast Error Abs Error 1997 313 3. 2 285 4 3 312 5. 4 339 6. 1998 1 359 7 320 356 385 6. 10 1999 396 367 11 397 12 423 13 14 2000 1 15 2000 3412M4QUESTIONS: Quarterly demand for a washing machine is as shown. 1. After obtaining initial estimates for level, trend, and seasonal factors. forecast the demand for the first quarter of year III using Winter's model with a 6- - 0,25 where x is the last two digits of your student number. 2. Make a tracking signal analysis for the forecast and evaluate Maks Year I II Quarter 1 2 3 4 1 2 3 4 Demand 1900 1224 4000 5600 4800 1048 6200 8000Q.No.04. What does BOM stands for? Why it is necessary for any firm to have correct forecast of BOM?
- QUESTION TWOGM Motors of Lusaka produces electronic motors for power actuated values for block makers in Lusaka. The GM Motors has been in operational for a year now and Mr. Banda, the plant manager, thinks that the growth in sales will continue for the years to come. Mr. Banda wants to develop a long range forecast to be used to plan facility requirements for the next three years. The sales records for the past ten years have been accumulated; Years Annual Sale (K’000)2007 10002008 13002009 18002010 20002011 20002012 20002013 22002014 26002015 29002016 3200 Required:a) Develop a regression equation for predicting the sales for the electronic motors. b) Use the regression equation to predict the sales for the next three year. c) Find the relationship between the sales and the years. Explain what your finding means. 2. A firm uses simple exponential smoothing with a=0.1…If the forecasted value of the time series variable for one period is 28.5 and the actual value observed for the same period is 32, what is the forecast error for that period? Question 19 options: 3.5 2 -3.5 4Part B Three-period Four-period Units Units Demanded Period weighted moving weighted moving Demanded Three-period weighted moving average forecast average forecast average forecast Four-period weighted moving average forecast 24 2 25 60 28 50 49 S50 4 32 26.33 46 4.90 39,80 40 41 5 35 29.50 28.6 38 35 38 32.83 31.7 30 32 28 25 26,93 250 es 7 41 36.00 34.9 24 20 8 46 39.00 38 49 43.00 41.8 10 10 53 46.67 45.4 50.50 49.2 1 2 3 4 5 6 7 8 9 10 11 1. Make a comparative analysis out of your answers in the plotted data. (3-5 sentences)
- Question 2 Historical demand for gulab jamun from a sweet stall on Commercial Road is as displayed in the table. Month Demand (orders) January 66,753 February 67,686 March 68,641 April 68,979 May 69,278 June 69,577 July 69,602 August 70,348 September 70,806 October 71,011 November 71,819 December 72,752 What is the forecast for June using Holt's model with an alpha of 0.1 and a beta of 0.2? 69121 69612 70564 63545 Full explain this question text typingQuestion 1 ) The monthiy sales Of yamizí Battery company are asfollows:- Month Jales 2000 2100 1500 1400 1300 Calcuiate fore cost sales for June using each of the fo llowing method: - i) Naive Method 1M 3 Month Simple moving averoger Ti) Exponentral smoothing using an a =0:3 cand may forecast of 1600 units.QUESTION THREE (a) The actual demand of a product for 6 months are summarized in Table below: Actual Demand Values Month ( ) t Demand ( ) tD 1 300 2 450 3 700 4 900 5 1200 6 1400 iv. Compute the mean absolute deviation. v. Mean absolute percent error (MAPE)
- B: Find forecasting error from the following table by using Tracking Signal. Period Actual Demand Forecasted Demand 1 8 10 2 10 10 3 7 10 4 13 10 5 9 10 6 12 10Month Demand Forecast Error Abs Error alpha 1 20 2 18 3 21 4 25 5 24 6 27 7 22 8 30 9 23 10 20 11 29 12 22 Mean Bias MAD (mean error) Problem 6: Maverick Jeans' demand manager decided to evaluate exponential smoothing. To maintain com- parability, she used the data from problem 6, copied below. 1 Month 2 3 Demand 20 18 21 25 4 5 24 6 7 8 9 10 11 12 27 22 30 23 20 29 22 Develop forecasts for months 5-12. Calculate the Bias and MAD. Use a starting forecast of 20 for month 4 and an alpha value of 0.2. (Note: Adjust all cell values to two decimal points.)Part C Exponential Exponential Gasoline Demand Gasoline Month smoothed forecast smoothed forecast Exponential smoothed forecast (a = 0.25) Demand (a = 0.25) (a = 0.45) Exponential smoothed forecast (a = 0.45) Mar 900 920 920 1200 Apr May 755 915.00 911.00 1100 1000 650 875.00 840.80 g20 915.00 846 80 755 818.75 754.94 904.76 835.12 Jun 550 818.75 754.94 800 320 751.56 66272 645.74 746.83 Jul 625 751.56 662.72 650 600 550 Aug Sep 730 719.92 645.74 820 722.44 683.66 400 D Oct 1100 746.83 745.01 200 1 Nov 835.12 904.76 Mar Apr May Jun Jul Aug Sep Oct Nov 1. Make a comparative analysis out of your answers in the plotted data. (3-5 5 sentences)