Regression analysis and other inferential statistics.

Twenty movies from 1999 and 2000 are listed in the attached Excel sheet with data entered.

You should have four values (variables) for each movie. Two of the values are found through the Rotten Tomotoes website (www.rottentomatoes.com).  The 'Tomatometer' is the percentage of movie critics who liked the movie and the 'Audience' value is what website users thought of the movie.  Finally, there are values for Worldwide Gross (amount the movie made) and the Production Budget (how much the movie cost) for each movie.   

Now do the following:

1)  Plot four different regression graphs (X v Y): Tomatometer v Audience, Budget v Gross, Budget v Tomatometer, Audience v Gross and find the best-fit line equation and correlation coefficient (r-value) for each one.  X represents the independent variable and Y represents the dependent variable.

2)  Use the r-value and Table I (pg. 797 of your textbook) to determine if your best-fit lines are significant at 0.05 significant level. (use 18 degrees of freedom here)

3)  Calculate and interpret two 95% confidence intervals to estimate the true mean Budget value.  The first will assume normality and use a z-interval; the second will assume a t-interval.

4)  Finally do a write-up on your results including your regression graphs, your confidence intervals and hypothesis test, and answers to the following questions using your graphs:

A) Using regression, does it appear that critics and audience members agree on what a movie should be rated?  Why or why not?

B) Does it appear that large budgets lead to high-grossing movies?  That is, are larger budgets associated with higher grossing movies? Why or why not?

C) Does it appear that movie critics like high-budget movies?  In other words, is there a relationship between higher ratings and higher budgets?  Why or why not?

D) Are higher ratings by audience members associated with higher gross amounts earned by the movie? Why or why not?