Paste BIU . - MA . Merge & Center % Format Painter Undo Clipboard Font Alignment Number N14 V I X V fx A B C D The next tab of this Excel spreadsheet contains the NFL raw data for these problems. NFL data N Year (x) Rushing yards/Game (y) 1 1980 1275 In the National Football League, the philosophy for winning (rushing, passing, 1981 130.1 defense) seems to go through cycles. Consider a time series of the average 1982 117.8 3 number of rushing yards in the NFL per regular season from 1980 to 2008. 1983 129.7 1984 123.9 1) Make a time series plot. Is there evidence that the average rushing yards is trending 1985 124.9 5 in one direction? Describe the general movement of the series. 1986 118. 6 8 1987 123.9 2) Fit a first order autoregressive model [ AR(1) ] using y(t) as the response vanable 9 1988 121.4 7 and y (t-1) as the input variable. Record the regression equation. 10 1989 115.3 11 1990 113.9 12 1991 107.7 3) Based on the AR(1) model, forecast the average number of rushing yards in the 13 1992 110.5 9 NFL for the 2009 regular season. 14 1993 110 10 15 1994 104,3 4) Calculate the exponential smoothing models using Excel damping factors 0.8 and 16 1995 108.1 0.2 For each of the exponential smoothing models forecast the average number of 17 1996 109 11 rushing yards in the NFL for the 2009 season. 18 1997 113 12 19 1998 112.7 5) Calculate a moving average model using k=5 (Excel interval). Forecast the 20 1999 106.5 13 average number of rushing yards in the NFL for the 2009 season. 21 2000 112.6 14 22 2001 111.8 23 2002 116.1 15 24 2003 117.9 16 2004 116.6 17 26 2005 112.5 18 27 2006 117.3 19 28 2007 110.9 20 29 2008 114.6 21 30 22 23 24 Data Source: The Practice of Statistics for Business and Economics 3rd edition, Moore, Mccabe, Alwan, Craig, Duckworth