Lately I've been studying up on the math and technology associated with data science because there are so many interesting things going on. Despite taking many notes, I found myself learning certain important terms, seeing them again later, and then thinking "What was that again? P-values? Huh?"

So, I turned a portion of my notes into a glossary to make these things easy to look up when I wanted to remember them. I decided that I may as well publish this glossary in case others found it helpful, or if they had suggestions or corrections. And, when I found that the domain name datascienceglossary.org wasn't taken, I couldn't resist grabbing it.

Now it's up and ready for the world: datascienceglossary.org. I also took the opportunity to try out Bootstrap to see how easily it might make my new little website look presentable on Android and Apple phones and tablets in addition to bigger screens. It was pretty easy, especially after I found their documentation page. (In the past, I've found that many CSS frameworks that are supposed to make your life easier have horrible if any documentation--"just look out our fabulous examples" isn't enough; if the class values that we're supposed to assign to our HTML elements are packed with cryptic little abbreviations, then tell us what all the abbreviations stand for.)

I hope my data science glossary is useful to some people. I know it will be useful to me, especially the next time I forget what "P-value" means.

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