Colonial Case

CBC colonial Broadcasting Case Run regression he Regression Model For a detailed rendering of the variables and the defined statistical terms used in this report, see adjoin 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*circumstance + 0. 910*(SQRT)Stars + 8. 413*Log (Previous Rating) 10. 206 *Log (Competition) This equation accounts for 44. 3% of the observed variation in ratings, with a precedent defect of 1. 97 (see Annex 3 for full details). Assumptions for this model can also be found on the same Annex. Methodology Set up the model, choose the data The sample size of 88 observations is great than 30 and therefore sufficient to be considered representative of the entire population. Ratings was chosen as the most suspend dependent variable since the success of a network relies on how many people watch their inci dent program/movie. An initial multiple regression was then run with all the remaining non-transformed variables against ratings.This resulted in an familiarised R2 value of 36%, meaning the regression equation accounts for 36% of the observed variation in ratings. The standard error was 2. 04, and the t-stats showed that every explanatory variable was statistically relevant except ABN, Month and Day (see Annex 7 ). Intuitively, some data points possibly could have a non-linear relationship and different tests were performed to see what amiable of relationships existed. It was concluded that several did exist an