Usually, there is some confusion on the topic of Hypothesis Testing. A standard undergraduate class on this topic involves terms such as “null hypothesis”, “alternative hypothesis”, “power of the test”, “statistically significant”, “p<0.05”, etc., which can be misleading or misunderstood. Most of this is due to the fact that the Neyman-Pearson paradigm of Hypothesis Testing has been stipulated in science and engineering as the standard mindset when data-based decisions have to be made.

This has to change. The use of this paradigm without justification has led to a lot of confusion not only in students but in practitioners. Why should…

Roberto Cabal-López

MS in Probability and Statistics & BA in Actuarial Science. Today I’m a project manager for data driven projects.

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