11. a. Construct a time-series graph of the sales data for HeathCo's line of skiwear (see data in c5p1 1). Does there appear to be a seasonal pattern in the sales data? Explain why you think the results are as you have found. (c5p1 1) b. It seems logical that skiwear would sell better from October through March than from April through September. To test this hypothesis, begin by adding two dummy vari- ables to the data: a dummy variable Q1 = 1 for each first quarter (January, February, March) and Q1 = 0 otherwise; and a dummy variable Q4 = 1 for each fourth quarter (October, November, December) and Q4 = 0 otherwise. Once the dummy variables have been entered into your data set, estimate the following trend model: SALES bo + bi(TIME) + b2Q1 + b3Q4 Evaluate these results by answering the following: . Do the signs make sense? Why or why not? . Are the coefficients statistically different from zero at a 95 percent confidence level (one-tailed test)? . What percentage of the variation in SALES is explained by this model? c. Use this model to make a forecast of SALES (SF2) for the four quarters of 2017 and calculate the MAPE for the forecast period. Period SALES ($000) SF2 2017Q1 334,271 2017Q2 328,982 2017Q3 317,921 2017Q4 350, 1 18 d. Prepare a time-series plot of SALES (for 2007Q1 through 2016Q4) along with SF2 (for 2007Q1 through 2017Q4) to illustrate how SALES and SF2 compare.Period Sales Time Q3 Mar-07 72962 Jun-07 81921 Sep-07 97729 Dec-07 142161 Mar-08 145592 DO JAVIAWN Jun-08 117129 Sep-08 114159 Dec-08 151402 Mar-09 153907 9 Jun-09 100144 10 Sep-09 123242 11 Dec-09 128497 12 Mar-10 176076 13 Jun-10 180440 14 Sep-10 162665 15 Dec-10 220818 16 Mar-11 202415 17 Jun-11 211780 18 Sep-11 163710 19 Dec-11 200135 20 Mar-12 174200 21 Jun-12 182556 22 o o o - o o o - o o o - 0 0 0 - 0 0 0 - 0 0 0 - 0 0 0- ooooooooo-000-2 - o o o - OOOH OOOH OOOH OOO OOO OOO OOOOOOOOOHOOOR o - o o o - o o o - o o o - O o O - O O O - O O O - O O O - O O O - O O O - O O O - O O , Sep-12 198990 23 Dec-12 243700 24 Mar-13 253142 25 Jun-13 218755 26 Sep-13 225422 27 Dec-13 253653 28 Mar-14 257156 29 Jun-14 202568 30 Sep-14 224482 31 Dec-14 229879 32 Mar-15 289321 33 Jun-15 266095 34 Sep-15 262938 35 Dec-15 322052 36 Mar-16 313769 37 Jun-16 315011 38 Sep-16 264939 39 Dec-16 301479 40 Mar-17 41 Jun-17 42 Sep-17 43 Dec-17 44