Data thuggery 101: A few tools of the trade

Abstract

As researchers, we are trained to be critical of the research we consume, but even the most well trained eye can miss details hidden within reported statistics (both descriptive and inferential). Tools have been developed which can detect inconsistencies in reported statistics and even reconstruct plausible sample distributions. While nothing can replace the careful scrutiny of a research article in its entirety, these tools can help at any stage of the publication process by allowing readers to glean further insights into sample data not readily available within the text.

Mark Christopher Adkins

PhD Candidate

My research interests include Monte Carlo Simulations, statistical consulting, and statistical pedagogy.