When we run a statistical test, we almost always obtain a p-value. Many statistical tests will also generate a confidence interval. Unfortunately, many scientists report the p-value and ignore the confidence interval. As pointed by Rothman (2016) and the American Statistical Association, relying on p-values forces a false dichotomy between results that are significant and those that are non-significant. This
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Bias is everywhere, and as scientists we must protect ourselves from it at every turn. One area that is particularly prone to the influence of bias is data analysis. As humans we see patterns everywhere, even when they are not even there! As scientists, there is the added pressure–conscious or not–that we should find a result and if at all
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In a previous post we saw that t distributions with more degrees of freedom approximate the Normal distribution more closely, and degrees of freedom are increased by testing more subjects. How do degrees of freedom influence t values when calculating confidence intervals? The confidence interval about an effect indicates how the effect varies if the study is repeated many times.
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When we perform a t test or calculate confidence intervals about an effect for a small study, we specify a t value from one of a family of t distributions depending on the number of degrees of freedom. What are degrees of freedom in statistics? The number of degrees of freedom refers to the number of separate, relevant pieces of
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In a previous post, we saw that the number of subjects or samples in our study does not influence the rate of false-positive findings. In this post we will learn how sample size influences estimates of the size of studied effects. If the true effect of a medication is to reduce heart rate by 10 beats per minute, how well
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As scientists we collect data and look for patterns or differences. Because populations display variation and we are unable to collect data from all members of a population, statistical results will always possess a level of uncertainty. For example, it is common to set alpha to 0.05. This implies that if there is no difference or effect, there is a
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