A pharmacist has been monitoring sales of a certain over-the-counter pain reliever. Daily sales during the last 15 days were Day: Number 1 3 8 sold: 33 36 37 44 41 45 46 44 48 Day: Number 10 11 12 13...


A pharmacist has been monitoring sales of a certain over-the-counter pain reliever. Daily sales during the last 15 days were<br>Day:<br>Number<br>1<br>3<br>8<br>sold:<br>33<br>36<br>37<br>44<br>41<br>45<br>46<br>44<br>48<br>Day:<br>Number<br>10<br>11<br>12<br>13<br>14<br>15<br>sold:<br>49<br>44<br>45<br>45<br>53<br>52<br>a. Assume the data refer to demand rather than sales. Using trend-adjusted exponential smoothing with an initial forecast of 44 for<br>Day 8, an initial trend estimate of 2, and a = B = 3, develop demand forecasts for Days 9 through 16. Then compute the resultant MSE<br>using the error values from Days 8 through 15. (Round your intermediate period-by-period forecast and error values to 3 decimal<br>places. Round your final MSE answer to 3 decimal places.)<br>MSE<br>

Extracted text: A pharmacist has been monitoring sales of a certain over-the-counter pain reliever. Daily sales during the last 15 days were Day: Number 1 3 8 sold: 33 36 37 44 41 45 46 44 48 Day: Number 10 11 12 13 14 15 sold: 49 44 45 45 53 52 a. Assume the data refer to demand rather than sales. Using trend-adjusted exponential smoothing with an initial forecast of 44 for Day 8, an initial trend estimate of 2, and a = B = 3, develop demand forecasts for Days 9 through 16. Then compute the resultant MSE using the error values from Days 8 through 15. (Round your intermediate period-by-period forecast and error values to 3 decimal places. Round your final MSE answer to 3 decimal places.) MSE

Jun 01, 2022
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