F3 = A2 + T2 = 38.5+0.45 = 38.95. Expon. Smooth.. Trend-Adjusted Expon. Smooth. (c=0.5, B = 0.3) Period 1 2 3 4 5 6 7 8 9 10 11 12 13 Month Jan Feb Mar Apr. May Jun Jul. Aug. Sep. Oct. Nov. Dec. Jan Demand 37 40 41 37 45 50 43 47 56 52 55 54 ? a=0.5 37.00 37.00 38.50 39.75 38.38 41.69 45.84 44.42 45.71 50.86 51.43 53.21 53.61 At 37.00 38.50 39.98 38.87 42.03 46.56 45.84 47.05 52.15 53.28 55.15 55.56 Tt 0.00 0.45 0.76 0.20 1.09 2.12 1.27 1.25 2.41 2.02 1.98 1.51 Ft 37.00 37.00 38.95 40.73 39.06 43.12 48.68 47.11 48.31 54.56 55.30 57.13 57.07 B. Casual or explanatory methods X15 Simple Linear Regression Model y = a + bx a where a = intercept b = slope of the line x = time period y = forecast for demand for period x Nov = WMA 0.5(720)+0.3(678)+0.2(650)=693.4 4 3 bx xy - n(y)(x) b= Ex-n(x) Question: Given the data below, what is the simple linear regression model that can be used to predict sales in future weeks? Week Sales 1501 157 31 162 1661 51 177 1 2 4 41