Problem 12-20 Suppose that you have become concermed about the amount of copier

Question

Problem 12-20 Suppose that you have become concermed about the amount of copier paper used in your office after repeatedly running out of supplies. Your assistant keeps track of the number of reams (packages of 500 sheets) for 24 weeks, as 10 12 Reams of paper 232 263 271 248 235 261 207 243 237 293 243 260 17 Reams of paper 253 270 230 253 238 272 222 243 289 238 262 234 13 16 10 19 20 23 a-1. Calculate MFE, MAD and MAPE using simple exponential smoothing model with an alpha of 0.2 and an initial forecast for week 1 of 232. Use weeks 1-24 to compute the simple exponential smoothing forecast for each week. (Do not round intermediate calculations. Round your answers to 1 decimal place.) Smoothing MAD MAPE a-2. Calculate MFE, MAD and MAPE using a seasonally enhanced model. (Hint: compute deseasonalized time-series regression forecasts for each week. Then compute seasonal indices for Weeks 1-0 using these forecasts as the base. Next, using a four-week seasonal pattem, compute the average seasonal indices using the first two cycles of data (Weeks 1-3). Finally, apply these average seasonal indices to deseasonalized forecasts for Weeks 1-24 to compute the seasonally enhanced forecast for each week.) (Do not round intermediate calculations. Round your answers to 1 decimal place.) Smoothing MAD MAPE a-3. is a simple mocel or a trend or seasonaly enhanced model better? O Seasonally enhanced madel Simple exponential smoothing model

Explanation / Answer

MFE=9.913094/24=0.4

MAPE=0.1x 100=10

MAD=24.9

a-2 )

MFE=-1.64

MAPE=6.71

MAD=16.95

Week Reams of Paper Forecast Values Error 1 232 232 0 2 263 232 31 3 271 256.8 14.2 4 248 268.16 -20.16 5 235 252.032 -17.032 6 261 238.4064 22.5936 7 207 256.48128 -49.4813 8 243 216.896256 26.10374 9 237 237.7792512 -0.77925 10 293 237.1558502 55.84415 11 243 281.83117 -38.8312 12 260 250.766234 9.233766 13 253 258.1532468 -5.15325 14 270 254.0306494 15.96935 15 230 266.8061299 -36.8061 16 253 237.361226 15.63877 17 238 249.8722452 -11.8722 18 272 240.374449 31.62555 19 222 265.6748898 -43.6749 20 243 230.734978 12.26502 21 289 240.5469956 48.453 22 238 279.3093991 -41.3094 23 268 246.2618798 21.73812 24 234 263.652376 -29.6524

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