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Time series data (from 2000 to 2010) for the number of Super Bowl commercials that advertised films are reported in the following table and displayed

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Time series data (from 2000 to 2010) for the number of Super Bowl commercials that advertised films are reported in the following table and displayed on the corresponding time series piot below. (Source: "For Advertisers, the Biggest Game of the Year," Interactive graphic, The New York Times) Number of Ads Forecast Error Absolute Value of Forecast Error Squared Forecast Error Percentage Error Absolute Value of Percentage Error Year Forecast 2000 7 2001 7 7 0 0 0 0 7 4 16 36.36 35.36 2002 2003 2004 12 11 1 1 1 3.33 8.33 9 2005 10 9 1 1 1 10 10 2006 1 1 1 9.09 10 11 9.09 -83.33 2007 6 -5 5 25 83.33 2008 7 6 1 1 1 14.29 14.29 9 2009 2010 7 2 2 -20.57 20.57 20 18 16 14 12 Number of Ads for Films 10 O 8 4 2 0 2000 2002 2004 2006 2008 2010 Year A naive forecasting method is used to forecast the number of Super Bowl spots that advertise films. Specifically, the most recent number of ads is used as the forecast for the next year. Some of the forecasts, forecast errors, and other related measures are shown in the table. Complete the table by entering the forecast forecast error, and related measures for 2001 and 2010. (Round your answers for percentage error and absolute value of percentage error to two decimal places.) The mean forecast error = The naive forecasting method is the number of commercials The mean absolute error (MAE) - The mean squared error (MSE) - (Note: Use your table entries to compute the MAPE and round your answer to two The mean absolute percentage error (MAPE) - decimal places) A naive forecasting method is used to forecast the number of Super Bowl spots that advertise films. Specifically, the used as the forecast for the next year. Some of the forecasts, forecast errors, and other related measures are show by entering the forecast, forecast error, and related measures for 2001 and 2010. (Round your answers for percent percentage error to two decimal places.) The mean forecast error = the number of commercia The naive forecasting method is underforecasting The mean absolute error (MAE) overforecasting The mean squared error (MSE) neither underforecasting nor overforecasting The mean absolute percentage error (MAPE) = %. (Note: Use your table entries to compute the MAPE decimal places.) Grade It Now

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