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Problem: Southwestern University is experiencing a quickly expanding football program. As a result, attendance for home games is increasing and approaching capacity. It is in the best interest of SWU to forecast attendance to aid them in deciding when the best time to expand the present stadium, which now holds 54,000.

Data: The following data is from the past six seasons, 2002-2007.

Game

Year – Game – Opponent | Attendance | 2002-1 Baylor | 34200 | 2002-2 Texas | 39800 | 2002-3 LSU | 38200 | 2002-4 Arkansas | 26900 | 2002-5 USC | 35100 | 2003-1 Oklahoma | 36100 | 2003-2 Nebraska | 40200 | 2003-3 UCLA | 39100 | 2003-4 Nevada | 25300 | 2003-5 Ohio State | 36200 | 2004-1 TCU | 35900 | 2004-2 Texas Tech | 46500 | 2004-3 Alaska | 43100 | 2004-4 Arizona | 27900 | 2004-5 Rice | 39200 | 2005-1 Arkansas | 41900 | 2005-2 Missouri | 46100 | 2005-3 Florida | 43900 | 2005-4 Miami | 30100 | 2005-5 Duke | 40500 | 2006-1 Indiana | 42500 | 2006-2 North Texas | 48200 | 2006-3 Texas A&M | 44200 | 2006-4 Southern | 33900 | 2006-5 Oklahoma | 47800 | 2007-1 LSU | 46900 | 2007-2 Texas | 50100 | 2007-3 Prairie View A&M | 45900 | 2007-4 Montana | 36300 | 2007-5 Arizona State | 49900 |

An important thing to note is that the homecoming game of every season is the second home game (bold), and is always well attended. Also the forth home game always corresponds with a local festival that always draws from attendance (italics).

Summary of Forecasting Methods: Below is a table of the forecasting methods. The correlation coefficient, bias, mean absolute deviation (MAD), mean squared error (MSE), and mean absolute percent error (MAPE) are shown.

| Correlation | Bias | MAD | MSE | MAPE | Naïve | -- | 541.38 | 6865.52 | 69,856,200 | .19 | Moving Average

(3 periods) |

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