STATS:DATA+MODELS-W/DVD
STATS:DATA+MODELS-W/DVD
4th Edition
ISBN: 9780321986498
Author: DeVeaux
Publisher: PEARSON
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Chapter 19, Problem 32E
To determine

Check whether there is strong evidence of a home field advantage in professional football in its home town.

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For each of the time​ series, construct a line chart of the data and identify the characteristics of the time series​ (that is,​ random, stationary,​ trend, seasonal, or​ cyclical). Month    PercentApr 1972    4.97May 1972    5.00Jun 1972    5.04Jul 1972    5.25Aug 1972    5.27Sep 1972    5.50Oct 1972    5.73Nov 1972    5.75Dec 1972    5.79Jan 1973    6.00Feb 1973    6.02Mar 1973    6.30Apr 1973    6.61May 1973    7.01Jun 1973    7.49Jul 1973    8.30Aug 1973    9.23Sep 1973    9.86Oct 1973    9.94Nov 1973    9.75Dec 1973    9.75Jan 1974    9.73Feb 1974    9.21Mar 1974    8.85Apr 1974    10.02May 1974    11.25Jun 1974    11.54Jul 1974    11.97Aug 1974    12.00Sep 1974    12.00Oct 1974    11.68Nov 1974    10.83Dec 1974    10.50Jan 1975    10.05Feb 1975    8.96Mar 1975    7.93Apr 1975    7.50May 1975    7.40Jun 1975    7.07Jul 1975    7.15Aug 1975    7.66Sep 1975    7.88Oct 1975    7.96Nov 1975    7.53Dec 1975    7.26Jan 1976    7.00Feb 1976    6.75Mar 1976    6.75Apr 1976    6.75May 1976…
Hi, I need to make sure I have drafted a thorough analysis, so please answer the following questions. Based on the data in the attached image, develop a regression model to forecast the average sales of football magazines for each of the seven home games in the upcoming season (Year 10). That is, you should construct a single regression model and use it to estimate the average demand for the seven home games in Year 10. In addition to the variables provided, you may create new variables based on these variables or based on observations of your analysis. Be sure to provide a thorough analysis of your final model (residual diagnostics) and provide assessments of its accuracy. What insights are available based on your regression model?
I want to make sure that I included all possible variables and observations. There is a considerable amount of data in the images below, but not all of it may be useful for your purposes. Are there variables contained in the file that you would exclude from a forecast model to determine football magazine sales in Year 10? If so, why? Are there particular observations of football magazine sales from previous years that you would exclude from your forecasting model? If so, why?
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