Open Access. Powered by Scholars. Published by Universities.®
Articles 1 - 2 of 2
Full-Text Articles in Life Sciences
Making The Error Bar Overlap Myth A Reality: Comparative Confidence Intervals, Frank S. Corotto
Making The Error Bar Overlap Myth A Reality: Comparative Confidence Intervals, Frank S. Corotto
Georgia Journal of Science
Many interpret error bars to mean that if they do not overlap the difference is statistically “significant”. This overlap rule is really an overlap myth; the rule does not hold true for any conventional type of error bar. There are rules of thumb for estimating P values, but it would be better to show error bars for which the overlap rule holds true. Here I explain how to calculate comparative confidence intervals which, when plotted as error bars, let us judge significance based on overlap or separation. Others have published on these intervals (the mathematical basis goes back to John …
Editorial, Your Null Hypothesis Must Be False: Test It Anyway, Frank Corotto
Editorial, Your Null Hypothesis Must Be False: Test It Anyway, Frank Corotto
Georgia Journal of Science
A historical criticism of null hypothesis testing is that a null hypothesis cannot be correct in the first place. The reason that many nulls cannot be correct is that what makes a null hypothesis a null hypothesis is its infinite precision. Only an infinitely precise hypothesis can be used to generate an infinitely precise prediction, such as t will be zero. It is around that infinitely precise prediction that we would construct a probability density function. If you are thinking, I just want to know if the difference is significant, and if you mean important, a null …