Introduction: In the Movies data setLinks to an external site., we have several movie ratings from 3 websites: www.rottentomatoes.com, www.imdb.com, and meta-score ratings from www.metacritic.com. In this project we will investigate the relationship between these rating systems.

Research question: Which is a better predictor of Rotten Tomatoes movie ratings, IMDb ratings or Metascore ratings?

Investigate this question using the data set MoviesLinks to an external site.. Support your answer using concepts from Modules 8 and 9.

For the variable that correlates with Rotten Tomatoes ratings most strongly (Notice that this is just for ONE of the variables), predict the Rotten Tomatoes rating. If IMDb is more strongly correlated, predict the Rotten Tomatoes rating for a movie that has an IMDb rating of 7. If Metascore correlates more strongly, predict the Rotten Tomatoes rating using a Metascore of 80. Use Unit 4 concepts to comment on the accuracy of your prediction.

The goal of this project is to answer the research question AND demonstrate your understanding of concepts in Unit 4. So show your work where appropriate and include explanations of general concepts.

Assignment Requirements Checklist:

• Identify the explanatory and response variables. Use technology to create appropriate scatterplots that facilitate easy visual comparison.
• Describe the form, direction and strength of the relationship between the variables. Identify any potential outliers.
• Discuss the concept of correlation. Use technology to calculate correlation coefficients to choose the best predictor of Rotten Tomatoes ratings.
• Use technology to find the equation of the regression lines (do this for BOTH). Interpret the slopes of the regression lines in the context of this data.
• Use the regression lines to make a prediction. If IMDb is more strongly correlated, predict the Rotten Tomatoes rating for a movie that has an IMDb rating of 7. If Metascore correlates more strongly, predict the Rotten Tomatoes rating using a Metascore of 80. Show your calculations.
• Comment on the accuracy of the prediction using r.