I just finished a pretty interesting book on this topic: "The Cult Of Statistical Significance": http://www.amazon.com/Cult-Statistical-Significance-Economics

I just finished a pretty interesting book on this topic: "The Cult Of Statistical Significance": http://www.amazon.com/Cult-Statistical-Significance-Economics-Cognition/dp/0472050079/ref=sr_1_1?ie=UTF8&qid=1428371506&sr=8-1&keywords=statistical+significance http://www.amazon.com/Cult-Statistical-Significance-Economic... It basically goes through a bunch of examples, mostly in Economics, but in medicine also (Vioxx) where statistical significance has failed us and people have died for it. As someone who works with statistics for a living, I found to book interesting - but it was pretty depressing to find out that most scientist are using t-test and p-values because it seems to be the status quo and it is the easiest way to get published. The authors of this book suggest a few different things -- publishing the size of your coefficients and using a loss function. In the end, they make the point that statistical significance is different than economic significance, political significance, etc.