In case you found this page first, click here to read the first page of this article.
This section is mostly going to be an information dump that will only be of interest to the 1% of the population that uses Minitab and/or R. (Hey, anyone want to teach me SAS?) I add a bit more commentary, and wanted to include this section to support the analysis. But the heavy lifting of the interpretation is left to you.
First, here is the Minitab output for both the 2011 and 2010 data sets. Notice that there is a higher coefficient for RT and a higher R2 when the regression model is based on the 2010 dataset.
Of course, these models don’t satisfy the necessary assumptions. There is no multicollinearity, and there is sufficient linearity. But the normality assumption is probably violated and there is definite heteroscedasticity.
To counteract this, a transformation of the dependent variable Y^(1/3) is needed. This transformation yields a better fit, but the transformation is much harder to explain than a one-unit increase on both sides of the equation, so I stuck with the basic regression model on the first page. There is some benefit to using polynomial regression, especially with the theater count. But since this model is a good fit without raising anything else to a power, I left it at this.
The Minitab output and relevant plots for the transformed regression model follows.