Question

Run a multiple regression where the dependent variable is ratings and the independent variables are star and fact. Use data from CBC only. CBC Management has several questions: Which has more impact on a movie’s rating: Being fact-based or having one star? How much does each of these factors change the ratings? How well does this regression analysis explain the ratings? Justify your answers referring to the relevant figures. Are either, both, or neither of the independent variables significantly related to the ratings at 95% confidence? Justify your answers referring to the relevant figures.

Answer 1

Answer:

See explaination

Step-by-step explanation:

See attachment for diagram

The r value is 0.373 (low). This implies a weak correlation between the dependent and independent variables for this sample.

The overall p- value for the regression model is 0.0017. This implies that at least one of the two independent variables (x1 or x2) in the model is significant predictor of the dependent variable y.

p- values for the both "Fact" and "Star" are < 0.05. This means both the independent variables are significant predictors of the "Rating" at 95% confidence level. The variable "Fact" is significant at 99% level of confidence also. This means the rating viewers award to a movie depends upon both the storyline (fact or Fiction) and the presence or absence of stars.

Expected rating for a fact based movie with no stars = 1.7991(1) + 1.2586(0) + 12.5685 = 14.37

Expected rating for a fiction based movie with a star = 1.7991(0) + 1.2586(1) + 12.5685 = 13.83

So, one may expect a fact based movie without any stars to get better ratings than a fiction based movie with one star.