Things we still haven't learned (so far).

Null hypothesis significance testing (NHST) is like an immortal horse that some researchers have been trying to beat to death for over 50 years but without any success. In this article we discuss the flaws in NHST, the historical background in relation to both Fisher's and Neyman and Pearson's statistical ideas, the common misunderstandings of what p < .05 actually means, and the 2010 APA publication manual's clear, but most often ignored, instructions to report effect sizes and to interpret what they all mean in the real world. In addition, we discuss how Bayesian statistics can be used to overcome some of the problems with NHST. We then analyze quantitative articles published over the past three years (2012-2014) in two top-rated sport and exercise psychology journals to determine whether we have learned what we should have learned decades ago about our use and meaningful interpretations of statistics.