3616 words 15 pages
Executive Summary
Colonial Broadcasting Co (CBC), a major American television network, must determine which of the different factors plays a key role in optimizing the ratings of its movie. The following report contains statistical analysis on the different relationships between the factors influencing ratings.
The Regression Model
For a detailed description of the variables and the defined statistical terms used in this report, see [ Annex 1 ]. Based on the sample data provided and the statistical analysis, the following regression equation has been derived:
Ratings = 13.729 - 1.540*BBS + 1.281*Winter + 1.164*Sunday +1.593*Monday + 1.854*Fact + 0.910*(SQRT)Stars + 8.413*Log (Previous Rating) - 10.206
Factors that have a positive but diminishing effect on ratings are the following: stars and previous rating. Both are non-linear as seen in the model (see Annex 3). The network should not use the BBS station and be cautious of the competitor ratings as these can diminish the movie’s ratings. However it is still highly recommended that more data points are gathered because the adjusted R2 tells us that the model is not an accurate predictor of future ratings/performance.
Impact of Different Networks
Based on some analysis, broadcasting the shows in different stations could possibly influence the ratings. In particular, a movie shown on the BBS network will decrease the ratings by 1.540 as suggested in the final model (see Annex 3). This is equivalent to roughly 1,418,340 viewers (1.540*921,000).
Based on the t-stat, p-value and confidence interval on the regression model (see Annex 9 for full details), using the ABN station does not have a profound effect on the rating of the movie. Had the tests indicated that the ABN network would increase ratings, then that would be an additional 0.983 worth or 905,343 (0.983*921,000) people. The best course of action for CBC, based on the tests, is to run the movie on its network rather than on BBS and ABN.
Predicting the Outcome of Replacing Josette and Yvette
Based on the model, using the previous ratings variable should have an effect of 0.1857 for every unit. This means that if the previous rating is 1, then this shall add

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