1) Identify the monthly seasonal indexes for the following three years of expenses for a six unit apartment house in southern florida.Use a 12 month moving average calculation Month Jan Feb Mar Apr May June July Aug Sep Oct Nov Dec Year 1 2) 30) Year2 170 180 205 230 240 315 360 290 240 240 230 195 Year 3 180 205 215 245 265 330 400 335 260 270 255 220 30) 195 210 230 280 290 390 420 330 290 295 280 250 With a smoothing constant of =0.2, equation (6.2) which is below shows that the forecast for the 13th week of the gasoline sales data from ta F13 = 0.2Y12+0.8(0.2Y11 +0.8F11) =0.2Y12+0.16Y11+0.64F11 a) Make use of the fact that F11=0.2Y10+0.8F10 ( and similarly for F10 and F9) and continue to expand the expression for F13 umntil you b) Refer to the coefficients or weights for the past data values Y12,Y11,Y10,Y9 and Y8What observation can you make about how exponen m table 6.1 which table is in 29 problem is given by F13 =0.2 Y12+.8F12.How ever ,the forecasts for week 12 is given by F12=0.2Y11+0.8F11.Thus we could combinee these two resul ou have written it in terms of the past data values Y12,Y11,Y10,Y9, and T8 and the forecast for the period 8 nential smoothing weights past data vlues in arriving at new forecasta?Compare this weighting pattern with the weights pattern of the moving averages method. sults to write the forecasts for the 13th week as 1) Identify the monthly seasonal indexes for the following three years of expenses for a six unit apartment house in southern florida.Use a 12 month moving average calculation Month Jan Feb Mar Apr May June July Aug Sep Oct Nov Dec Year 1 2) 30) Year2 170 180 205 230 240 315 360 290 240 240 230 195 Year 3 180 205 215 245 265 330 400 335 260 270 255 220 30) 195 210 230 280 290 390 420 330 290 295 280 250 With a smoothing constant of =0.2, equation (6.2) which is below shows that the fore F13 = 0.2Y12+0.8(0.2Y11 +0.8F11) =0.2Y12+0.16Y11+0.64F11 a) Make use of the fact that F11=0.2Y10+0.8F10 ( and similarly for F10 and F9) and continue to expand the expression for F13 umntil you b) Refer to the coefficients or weights for the past data values Y12,Y11,Y10,Y9 and Y8What observation can you make about how exponen 6.1 Table Week 6.2 Table Sales ( 1000s of Gallons) 1 2 3 4 5 6 7 8 9 10 11 12 17 21 19 23 18 16 20 18 22 20 15 22 orecast for the 13th week of the gasoline sales data from table 6.1 which table is in 29 problem is given by F13 =0.2 Y12+.8F12.How ever ,the forecasts for week 12 is given by F12=0 ou have written it in terms of the past data values Y12,Y11,Y10,Y9, and T8 and the forecast for the period 8 ential smoothing weights past data vlues in arriving at new forecasta?Compare this weighting pattern with the weights pattern of the moving averages method. 2=0.2Y11+0.8F11.Thus we could combinee these two results to write the forecasts for the 13th week as 1) Identify the monthly seasonal indexes for the following three years of expenses for a six unit apartment house in southern florida.Use a 12 month moving average calculation Month Jan Feb Mar Apr May June July Aug Sep Oct Nov Dec Year 1 2) 30) Year2 170 180 205 230 240 315 360 290 240 240 230 195 Year 3 180 205 215 245 265 330 400 335 260 270 255 220 30) 195 210 230 280 290 390 420 330 290 295 280 250 With a smoothing constant of =0.2, equation (6.2) which is below shows that the forecast for the 13th wee F13 = 0.2Y12+0.8(0.2Y11 +0.8F11) =0.2Y12+0.16Y11+0.64F11 a) Make use of the fact that F11=0.2Y10+0.8F10 ( and similarly for F10 and F9) and continue to expand the expression for F13 umntil you have written it in ter b) Refer to the coefficients or weights for the past data values Y12,Y11,Y10,Y9 and Y8What observation can you make about how exponential smoothing weigh 6.1 Table Week Sales ( 1000s of Gallons) 1 2 3 4 5 6 7 8 9 10 11 12 17 21 19 23 18 16 20 18 22 20 15 22 6.2 Table Week Times SerieMoving Ave Forecast Squared Fo 1 17 2 21 3 19 4 23 19 4 16 5 18 21 -3 9 6 16 20 -4 16 7 20 19 1 1 8 18 18 0 0 9 22 18 4 16 10 20 20 0 0 11 15 20 -5 25 12 22 19 3 9 Total 0 92 eek of the gasoline sales data from table 6.1 which table is in 29 problem is given by F13 =0.2 Y12+.8F12.How ever ,the forecasts for week 12 is given by F12=0.2Y11+0.8F11.Thus we could combinee the rms of the past data values Y12,Y11,Y10,Y9, and T8 and the forecast for the period 8 ghts past data vlues in arriving at new forecasta?Compare this weighting pattern with the weights pattern of the moving averages method. orecast error hese two results to write the forecasts for the 13th week as