Fundamental Statistical Methods for Engineers

In today's data-rich engineering environments, a solid grasp of fundamental statistical methods is essential. Engineers routinely face variability in materials, processes, and measurements — and statistics provides the tools to…

The Primary Outcome Is Positive — Is That Good Enough?

Clinical trial findings are often simplified into a binary conclusion, focusing on a P value of less than 0.05 for a treatment difference. However, a more nuanced interpretation requires examining…

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Statistical Terminology for ANOVA (lm), glm, glmm & Beyond

I would like to propose alternatives to what is unfortunately very common in scientific papers "An ANOVA was done/..." Hopefully, the terminology below should help investigators improving the reporting of…

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Statistical Reporting Needs to Convey More Details for Clarity

Today I would like to focus on the quality of information associated with simple statistical methods commonly used in the biomedical sciences and how they are reported in scientific publications.…

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Tests for Detecting Non-Normality – Good Practices & Pitfalls

There are several normality tests: Shapiro-Wilk, Kolmogorov-Smirnov, Anderson-Darling, Liliefors, Jarque-Bera, Anscombe-Glynn, Cramer--von Mises, etc. Normality Tests @Statistical.Solutions Pitfalls ♦️ "Non-" Normality tests" vary in the type of departures from normality…

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