Pharmaceuticals is a small to mid size pharmaceutical company. The accounting department began extending its historical records by recording the sales volume for each month over the past four years, starting in January.

The company engages in various kinds of direct to consumer advertising and, until recently, has never studied the effect its advertising dollars have on sales, although some data had also been collected. Their hope was that after several months the collected data could be examined to possibly reveal any relationships that would help in future advertising expenditures.

The accounting department besides extending its historical records by recording the sales volume for each month, they also collected advertising dollars for both magazine and TV spots. They also recorded both these values lagged one and two months. This was done because some people on the executive committee thought that sales might lag advertising expenditures rather than respond in the month the ads appeared. It was also believed that sales experienced a seasonal effect and management further wondered about any trend in the sales volume. Finally, it was believed that Alomegas advertising dollars might have an effect on its major competitors advertising budgets the following month. For each following month it was decided that competitors advertising could be classified as: (1): little; (2): a moderate amount, or; (3): a great amount.

After a few months of data collection and analysis of past records, the accounting department completed an Excel file using the following variables:

Sales dollars

Magazine advertising dollars

TV advertising dollars

Code 1, 2, or 3 to indicate competitors advertising efforts the following month.

The data is in thetable below.

1.I build a 3-period moving average model.

2. build an exponential model, using = .1.

3. Evaluate the two above models, i.e., which one is the best and explain why.

4. build a regression model with only the time series componentstrend and seasonal components.

5., evaluate the above model, i.e., is it a good model? If so, why, or if not, why? Consider all the appropriate tests, = 0.05. (explain your conclusions).

6. Using the model you developed in 1 (of part 2), i forecast the next 12 months (in the future).

7.Build a regression model with only the causal variables, paper advertising, tv advertising, and competitors advertising (complete).

8. evaluate the above model, i.e., is it a good model? If so, why, or if not, why? Consider all the appropriate tests, = 0.05. (explain your conclusions).

9. Compare the models, moving average, exponential smoothing, classical decomposition, regression with time series and regression with causal variables, which one is the best and explain why.

Sales Paper 425075 75253 315305 15036 432101 134440 357191 119740 347874 135590 435529 189636 299403 9308 296505 41099 426701 9391 329722 9421 281783 1818 166391 672 629404 548704 263467 52819 468612 2793 313221 27749 444404 21887 386986 1110 414314 436 253493 1407 484365 376650 305989 122906 315407 15138 182784 5532 655748 544807 270483 43704 429480 5740 260458 9614 528210 1507 3798561 13620 4720581 101179 254516 80309 551354 335768 335826 91710 320408 9856 276901 107172 455136 299781 247570 21218 732005 157 357107 12961 453156 333529 320103 178105 451779 315564 249482 80206 744583 5940 421186 36819 397367 234562 269096 71881 Compete Month 114433 Weak January 63599 Moderate February 64988 Moderate March 66842 Weak April 39626 Moderate May 107503 Strong June 97129 Strong July 56404 Moderate August 260576 Strong September 243523 Strong October 75473 Strong November 19037 Moderate December O Moderate January 78799 Moderate February 175906 Weak March 49616 Weak April 119720 Moderate May 114293 Moderate June 177370 Strong July 11345 Moderate August 7020 Weak September 27880 Moderate October 66800 Strong November 88576 Strong December 166178 Moderate January 134206 Moderate February 137890 Weak March 37520 Weak April 145200 Weak May 108770 Moderate June 90286 Moderate July 24461 Moderate August 7593 Strong September 37581 Strong October 73261 Strong November 40697 Moderate December 8133 Strong January 5867 Moderate February 1125864 Moderate March 125226 Weak April o Weak May O Moderate June 11526 Moderate July 23063 Moderate August 1217488 Weak September 94139 Weak October 94139 Weak November 138134 Weak December Sales Paper 425075 75253 315305 15036 432101 134440 357191 119740 347874 135590 435529 189636 299403 9308 296505 41099 426701 9391 329722 9421 281783 1818 166391 672 629404 548704 263467 52819 468612 2793 313221 27749 444404 21887 386986 1110 414314 436 253493 1407 484365 376650 305989 122906 315407 15138 182784 5532 655748 544807 270483 43704 429480 5740 260458 9614 528210 1507 3798561 13620 4720581 101179 254516 80309 551354 335768 335826 91710 320408 9856 276901 107172 455136 299781 247570 21218 732005 157 357107 12961 453156 333529 320103 178105 451779 315564 249482 80206 744583 5940 421186 36819 397367 234562 269096 71881 Compete Month 114433 Weak January 63599 Moderate February 64988 Moderate March 66842 Weak April 39626 Moderate May 107503 Strong June 97129 Strong July 56404 Moderate August 260576 Strong September 243523 Strong October 75473 Strong November 19037 Moderate December O Moderate January 78799 Moderate February 175906 Weak March 49616 Weak April 119720 Moderate May 114293 Moderate June 177370 Strong July 11345 Moderate August 7020 Weak September 27880 Moderate October 66800 Strong November 88576 Strong December 166178 Moderate January 134206 Moderate February 137890 Weak March 37520 Weak April 145200 Weak May 108770 Moderate June 90286 Moderate July 24461 Moderate August 7593 Strong September 37581 Strong October 73261 Strong November 40697 Moderate December 8133 Strong January 5867 Moderate February 1125864 Moderate March 125226 Weak April o Weak May O Moderate June 11526 Moderate July 23063 Moderate August 1217488 Weak September 94139 Weak October 94139 Weak November 138134 Weak December