My students often look up statistical methods on Wikipedia. Sometimes they admit this with a hint of embarrassment in their voices. They are right to be cautious when using Wikipedia (not all pages are well-written) and I’m therefore pleased when they ask me if there are other good online resources for statisticians.

I usually tell them that Wikipedia actually is very useful, especially for looking up properties of various distributions, such as density functions, moments and relationships between distributions. I wouldn’t cite the Wikipedia page on, say, the beta distribution in a paper, but if I need to check what the mode of said distribution is, it is the first place that I look. While not as exhaustive as the classic Johnson & Kotz books, the Wikipedia pages on distributions tend to contain quite a bit of surprisingly accurate information. That being said, there are misprints to be found, just as with any textbook (the difference being that you can fix those misprints – I’ve done so myself on a few occasions).

Another often-linked online resource is Wolfram MathWorld. While I’ve used it in the past when looking up topics in mathematics, I’m more than a little reluctant to use it after I happened to stumble upon their description of significance tests:

A test for determining the probability that a given result could not have occurred by chance (its significance).

…which is a gross misinterpretation of hypothesis testing and p-values (a topic which I’ve treated before on this blog).

*the*place to go if you have a statistics question that you are unable to find the answer to, regardless of whether its about how to use the t-test or about the finer aspects of LeCam theory. I strongly encourage all statisticians to add a visit to Cross Validated to their daily schedules. Putting my time where my mouth is, I’ve been actively participating there myself for the last few months.

*Grundbegriffe*), I still haven’t gathered my guts to venture beyond the English version.