Kass Co-Authors 10 Simple Rules To Use Statistics Effectively

Under growing pressure to report accurate findings as they interpret increasingly larger amounts of data, researchers are finding it more important than ever to follow sound statistical practices. For that reason, a team of statisticians including Carnegie Mellon University's Robert E. Kass wrote "Ten Simple Rules for Effective Statistical Practice. Published in PLOS Computational Biology for the journal's popular "Ten Simple Rules” series, the guidelines are designed to help the research community - particularly scientists who aren't statistical experts or without a dedicated statistician as part of their team - understand how to avoid the pitfalls of well-intended, but inaccurate statistical reasoning. "A central and common task for us as research investigators is to decipher what data are able to say about the problems we are trying to solve,” wrote Kass, professor of statistics and machine learning and interim co-director of the Center for the Neural Basis of Cognition , and his co-authors. "Statistics is a language constructed to assist this process, with probability as its grammar. They continued, "While rudimentary conversations are possible without good command of the language (and are conducted routinely), principled statistical analysis is critical in grappling with many subtle phenomena to ensure that nothing serious will be lost in translation and to increase the likelihood that your research findings will stand the test of time. The rules, which were made available online June 9, have received an extraordinary amount of attention so far with more than 38,000 page views, already making it one of the top 20 most viewed papers in the series, which includes about 60 total papers.