Mathematical statistics and probability is hard. It often involves what, at a first glance, involves complicated calculations and the sheer volume of data coming out of some studies can often be hard to interpret, even if you know all of the mathematics behind it. Although it is important to understand the math, it is equally important (or perhaps even more important) to understand what the results mean and don’t mean. It is easy to get dazzled by fancy mathematics or over-interpret results to mean something they really do not. Therefore, a basic understanding of statistical fallacies should be a part of every scientific skeptics toolbox or baloney detection kit.
Here is a list of the most common statistical fallacies, what they are and how to combat them.
1. Confusing correlation with causation
A correlation is when two variables vary together, whereas. For instance, ice cream sales may increase in the…
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