Summary
In this first chapter, we've learned about summary statistics and the value of distributions. We've seen how even a simple analysis can provide evidence of potentially fraudulent activity.
In particular, we've encountered the central limit theorem and seen why it goes such a long way towards explaining the ubiquity of the normal distribution throughout data science. An appropriate distribution can represent the essence of a large sequence of numbers in just a few statistics and we've implemented several of them using pure Clojure functions in this chapter. We've also introduced the Incanter library and used it to load, transform, and visually compare several datasets. We haven't been able to do much more than note a curious difference between ...
Become an O’Reilly member and get unlimited access to this title plus top books and audiobooks from O’Reilly and nearly 200 top publishers, thousands of courses curated by job role, 150+ live events each month,
and much more.
Read now
Unlock full access