Fallacies and Errors in Inferential Statistics
January 26, 2013 12:17 AM Subscribe
I have recently been introduced to the concept of pseudoreplication as a mistake that people often make when using inferential statistics to evaluate treatment outcomes. My field (evolutionary and conservation biology) makes heavy use of inferential statistics, including techniques that are vulnerable to pseudoreplication, yet nowhere in my formal education have I been taught about how poor experimental design and lack of statistical rigor can lead to fallacies like this. My personal statistical proficiency is poor, but I am working to remedy that. To that end, could folks help me by identifying and ideally explaining whatever other potential pitfalls you can think of, and explaining how they can be avoided through careful experimental design and data-analysis?