Statistics Done Wrong by Alex Reinhart.
From the post:
If you’re a practicing scientist, you probably use statistics to analyze your data. From basic t tests and standard error calculations to Cox proportional hazards models and geospatial kriging systems, we rely on statistics to give answers to scientific problems.
This is unfortunate, because most of us don’t know how to do statistics.
Statistics Done Wrong is a guide to the most popular statistical errors and slip-ups committed by scientists every day, in the lab and in peer-reviewed journals. Many of the errors are prevalent in vast swathes of the published literature, casting doubt on the findings of thousands of papers. Statistics Done Wrong assumes no prior knowledge of statistics, so you can read it before your first statistics course or after thirty years of scientific practice.
Dive in: the whole guide is available online!
Something to add to your data skeptic bag.
As a matter of fact, a summary of warning signs for these problems would fit on 81/2 by 11 (or A4) paper.
Thinking when you show up to examine a data set, you have Statistic Done Wrong with the web address on the back of your laminated cheat sheets.
Part of being a data skeptic is intuiting where to push so that the data “as presented” unravels.
I first saw this in Nat Torkington’s Four short links: 30 October 2013.