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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When a p value that fails to reach a threshold is reported, investigators sometimes imply there is a “trend towards statistical significance”. This interpretation expresses the view that if more subjects had been tested, the p value would have become more significant. Epidemiologists Wood and colleagues examined the probability of how the p value of a treatment effect changes when
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In our previous post, we revisited the Ioannidis argument on Why most published research findings are false. Other factors such as p-hacking can also increase the chance of reporting a false-positive result. Such results are associated with a p-value deemed to be statistically significant, but the underlying hypothesis is in fact false. Researcher degrees of freedom As scientists, we have
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