More is not better–when statistics turn bad (it’s just not as entertaining as when animals do)
As with everything, more is not usually better. In statistics, more actually makes you more prone to being accidentally wrong (or, in statistics-lingo, spurious). Today, I’d like to talk about a basic concept that is taught to students in their introductory statistics courses (and hence, you would think, most researchers): The effect of multiple significance testing. Read More...
This episode is brought to you by the letter p
What does the p-value actually mean? Read More...
Beta-alanine revisited: Failing to plan, or planning to fail?
In the past 2.5 years, a few more studies on beta-alanine have emerged. As I’ve written before, my goal isn’t to become the anti-beta-alanine blogger, but I do feel that watching this supplement develop from its relative inception to its current state does provide an interesting prototype for how similar products develop a strong following despite the limitations on the research available to support (or not support) its use. Read More...
The most successful people aren’t necessarily the ones you want to listen to
I recently joined Twitter. Mostly, because I wanted to see what the fuss was about and it seemed like a neat way to tap into yet another network. The interesting thing about Twitter early on, is that (for those of us who have attention spans of gnats) that Twitter feed page doesn’t change very often unless you start following people’s Twitter feeds (I’m sorry, but “tweeps”? Seriously, no.) So I started searching for names of people I thought would be interesting to follow and whether they had feeds to follow or not. And on my journey through Google, I stumbled on this excerpt from someone I would consider to be one of the most impressive physique models in the world. I’ve broken them down, point by point instead of the entire crammed-in paragraph. but they are sequential (and I don’t think they’re taken out of context): Read More...