Associations and Correlations

▶ About the Book
Associations and correlations are perhaps the most used of all statistical techniques. Consequently, they are possibly also the most misused.

The problem is that the majority of people that work with association and correlation tests are not statisticians and have little or no statistical training. That's not a criticism, but simply an acknowledgement that most researchers, scientists, healthcare practitioners, and other investigators are specialists in things other than statistics and have limited – if any – access to statistical professionals for assistance.

Therefore, they turn to statistical textbooks and perceived knowledge among their peers for their training. I won't dwell too much on perceived knowledge, other than to say that both the use and misuse of statistics passes through the generations of researchers equally. There is a lot of statistical misinformation out there…

There are many statistical textbooks that explain everything you need to know about associations and correlations, but here is the rub: most of them are written by statisticians that understand, in great depth, how statistics work and they don't understand why non-statisticians have difficulty with stats – they have little empathy. Consequently, many of these textbooks are full of highly complex equations explaining the mathematical basis behind the statistical tests, are written with complicated
statistical language that is difficult for the beginner to penetrate, and they don't take into account that the reader just might be looking into statistics for the first time.

Ultimately, most statistics books are written by statisticians for statisticians.

In writing this book, I was determined that it would be different.

This is a book for beginners. My hope is that more experienced practitioners might also find value in it, but my primary focus here is on introducing the essential elements of association and correlation analyses. If you want the finer points, then you're plum out of luck – you won't find them here. Just the essential stuff. For beginners.

There's another issue I've noticed with most statistical textbooks, and I'll use a house building analogy to illustrate it.

When house builders write books about how to build houses, they don't write about hammers and screwdrivers. They write about how to prepare the foundations, raise the walls, and fit the roof. When statisticians do their analyses, they think like the house builder. They think about how to pre-process their data (prepare the foundations), do preliminary investigations to get a 'feel' for the data (raise the walls and see what the whole thing will look like), and, finally, they deduce the story of the data (making the build watertight by adding a roof).

Unfortunately, that's not how they write books. Most statistical textbooks deal with statistical tests in isolation, one by one. They deal with the statistical tools, not the bigger picture. They don't tend to discuss how information flows through the data, nor how to create strategies to extract the information that tells the story of the whole dataset.

Here, I discuss a holistic method of discovering the story of all the relationships in your data by introducing and using a variety of the most used association and correlation tests (and helping you to choose them correctly). The holistic method is about selecting the most appropriate univariate and multivariate tests and using them together in a single strategic framework to give you confidence that the story you discover is likely to be the true story of your data.

The focus here is on the utility of the tests and on how these tests fit into the holistic strategy. I don't use any complicated math (OK, well, just a little bit toward the end, but it's necessary, honest…), I shed light on complicated statistical language (but I don't actually use it – I use simple, easy-to-understand terminology instead), and I don't discuss the more complex techniques that you'll find in more technical textbooks.