Question

Thus, r_ (.9014) .8125, meaning that about 81% of the variability in sales can be explained by the regression model with advertising as the independent varia ble. Problems Nde ΡΧ mere te problem may be sch od with POM for Wrndows ardor Exco. 4.1 The following gives the number of pints of type B t wook of October 12 b) Use a 3-week weighted moving average, with weights of. 1, 3, and 6, using .6 for the most recent week. Forecast demand for blood used at Woodlawn Hospital in the past 6 weeks c) Compute the forecast for the weck of October 12 using exponential smoothing with a forecast for August 31 of 360 anda 2 Px PINTS USED September 7 September 14 12 3 4 5 67 8 9 10 11 7 9 5 9 13 8 12 13 911 7 410 381 368 374 a) Plot the above data on a graph. Do you observe any trend, b) Starting in year 4 and going to year 12, forecast demand using a) Eorecast the demand for the week of October 12 using aa 3-year moving average. Plot your forccast on the same graph September 28 cycles, or random variations? 5 as the original data. 3-week moving average. eek moving average

Answer 1

3-week moving average forecast of Week of Oct -12 = Average of last three months = (381+368+374)/3 = 374.33 pints

Weighted average forecast of 3 months = Sum of (Weights*actual of month) = 0.6*374+0.3*368+0.1*381= 372.90

Exponential Forecast below: Alpha = 0.2

where +1 = the forecast for the next period = actual demand in the present period F = the previously determined forecast for the present period c = a weighting factor referred to as the smoothing constant

For week of October 12 = 0.2 * 374 + (1-0.2) *374.33= 374.26

Week of	Pints used (At)	Forecast (Ft)
31-Aug	360	360.00
7-Sep	389	360.00
14-Sep	410	365.80
21-Sep	381	374.64
28-Sep	368	375.91
5-Oct	374	374.33
12-Oct		374.26

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