Assingment

7)Disney is grossing more over time because the p-value is positive.

Disney is grossing less over time because the p-value is positive.

Disney is grossing more over time because the p-value is negative.

Disney is grossing less over time because the p-value is negative.

Disney is grossing more over time because the coefficient is positive.

Disney is grossing less over time because the coefficient is positive.

Disney is grossing more over time because the coefficient is negative.

Disney is grossing less over time because the coefficient is negative.

Bookmark question for later

Can we rely on these results and expect to see something similar as new movies are added?

Bookmark question for later

Fill in all missing values of mpaa_rating with the value "Empty"

Create dummy code features to convert mpaa_rating to sets of numeric 0/1 features for all values except "Empty"

Run another MLR a few rows below the previous one using both days_since_release and all of the dummy codes you just created for mpaa_rating

What did the inclusion of these dummy coded mpaa_rating features do to the model fit?

Options:

1There is no way to tell from these results

2It made the model fit better

3Did not change it at all

4It made the model fit worse

17)Upload the Excel file containing the data and all of your regression models

7,17questions and read the instructions for both questions in assignment document.