Construct a table similar to Table P-14 with the natural logarithms of monthly sales. For example, the value for January 2000 is ln(154) = 5.037.
Table P-14

a. Perform an additive decomposition of ln(sales), assuming the model
Y = T + S + I.
b. Would you use the trend component, the seasonal component, or both to forecast?
c. Provide forecasts of ln(sales) for the remaining months of 2006.
d. Take the antilogs of the forecasts calculated in part c to get forecasts of the actual sales for the remainder of 2006.
e. Compare the forecasts in part d with those in Problem 14, part c. Which set of forecasts do you prefer? Why?

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Month 2000 2001 2002 2003 2004 2005 2006 January 154 200 223 346 518 613 628 February 96 118 104 261 404 392 308 March April May June 73 90 107 224 300 273 324 49 79 85 141 210 322 248 36 78 75 148 196 189 272 59 9 99 145 186 257 95 167 135 223 247 324 July August 169 169 211 272 343 404 September 210 289 335 445 464 677 October 278 347 460 560 680 858 November 298 375 488 612 711 895 December 245 203 326 467 610 664