Some background…

• So far, we’ve learned about measuring the success of a model based on how close it’s predictions come to the actual observations.
• The correlation coefficient is a tool that gives us a fairly good idea of how these predictions will turn out without having to make predictions on future observations.
• For this lab, we will be using the movie data set to investigate the following questions:

Which variables are better predictors of a movie’s audience_rating when the predictions are made using a line of best fit?

Correlation coefficients

• The correlation coefficient describes the strength and direction of the linear trend.

• It’s only useful when the trend is linear and both variables are numeric.