I'm not a statistician, but I found the following juxtaposition rather contradictory: >* Confidence intervals for the main results should always be included, b

I'm not a statistician, but I found the following juxtaposition rather contradictory: >* Confidence intervals for the main results should always be included, but 90% rather than 95% levels should be used >* When there is a meaningful null hypothesis, the strength of evidence against it should be indexed by the P value. The smaller the P value, the stronger is the evidence This sounded to me like "You shouldn't use P-values to decide, except when you do." (For non-mathy types, P values is 1-confidence, so they measure the same quantity). I think some of this stems from their strong voiced preference for Bayesian statistics (there's something of a civil war among statisticians between bayesian and classical statistics). I've never been able to swallow the Bayesian theories; they're just too weird for my feeble mind to grasp.