The Texas Tech Red Raider Athletic Department wants to develop its budget for the coming year using a forecast for football attendance. Football attendance accounts for the largest portion of its revenues and Athletic Director Kirby Hocutt believes attendance is directly related to the number of wins by the Red Raider football team. Kirby has accumulated average attendance figures for the past 8 years (shown below). Given the number of returning starters and the strength of schedule, Kirby believes the team will win at least seven games this year. Develop a Linear regression (Associative Model) equation for this data to forecast average attendance this year. Wins - 6 Attendance 36,300 40,100 41,200 53,000 44,000 45,600 39,000 47,500 - 6 7 7 0 A 46,891 0 B 47,525 0 C 48,384 O D 49,278 O E 50,517 Lubbock Emergency calls to theier 911 system for the past 24 weeks are shown below. Using a nave forecast, a 3-month moving average, a 3-month weighted moving average with weights of 0.6, 0.3, 0.1 (heaviest weights on the most recent months and exponential smoothing with alpha=0.2 and a first week forecast of 50 calls, determine the tracking signal for each method (use Excel on this problem to calculate the answer quickly). Which method has the best tracking signal in this situation and what is the tracking signal value? 5 6 10 12 50 WEEK CALLS WEEK CALLS 2 35 14 35 3 25 15 25 4 40 16 55 7 20 19 35 8 30 20 60 9 35 21 75 22 11 15 23 40 NA 55 55 50 O A Nave, 1.06 0 B 3-month Moving Average, 0.33 0 C 3-month Weighted Moving Average, 0.15 O D Exponential Smoothing, 0.40 O E 3-month Moving Average, 3.33 O F 3-month Weighted Moving Average, 2.85 O G Exponential Smoothing, 2.51 O H Nave, 2.12