Aa 1 1. a. Construct a time-series graph of the sales data for HeathCo's line of skiwear (see data in c5pl1 ). Does there appear to be a seasonal pattern in the sales data? Explain why you think the results are as you have found. (c5pll[ ) 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 variables 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 + 63Q4 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 350,118 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