Section 5.4 Conclusion
Subsection 5.4.1 Additional resources
An R script file of all R code used in this chapter is available here.
As we suggested in Subsection 5.1.1, interpreting coefficients that are not close to the extreme values of -1, 0, and 1 can be somewhat subjective. To help develop your sense of correlation coefficients, we suggest you play the 80s-style video game called, “Guess the Correlation,” at http://guessthecorrelation.com/ previewed in Figure 5.4.1.
Subsection 5.4.2 What’s to come?
In this chapter, you’ve studied the term simple linear regression, where you fit models that only have one explanatory variable. In Chapter 6, we’ll study multiple regression, where our regression models can now have more than one explanatory variable moving a little bit more advanced than the basic form of simple linear regression! In particular, we’ll consider two scenarios: regression models with one numerical and one categorical explanatory variable and regression models with two numerical explanatory variables. This will allow you to construct more sophisticated and more powerful models, all in the hopes of better explaining your outcome variable \(y\text{.}\)
