R gives you good diagnostic information to help you take the next step in your analysis, which is to visualize the results.
Statistics provides us with a method of investigation where other methods haven't been able to help, and their success or failure isn't clear to many people. If we see a correlation and think that the relationship is obvious, then we need to think again. Correlation can help people to insinuate causation. It's often said that correlation is not causation, but what does this mean? Correlation is a measure of how closely related two things are. We can use other statistical methods, such as structural equation modeling, to help us to identify the direction of the relationship, if it exists, using correlated data. It's a complex field in itself, and it isn't covered in this book; the main point here is to show that this is a complex question.
How does correlation help us here? For our purposes, the most interesting...
