Tag: reproducibility

Next in our series of commentaries on Makin and Orban de Xivry’s Common Statistical Mistakes, #6: Circular Analysis. (Previous posts: #1-2, #3 , #4, #5.) I was thinking of skipping this one entirely. It’s less dramatic than #5 or the upcoming #7, I’m not sure I fully understand the authors’ intent, and my seashore painting … Continue reading Comments on “Circular Analysis” — “Ten common statistical mistakes…” #6

Continuing our series of commentaries on Makin and Orban de Xivry’s article on common Statistical Mistakes, let’s look at #5: Small Samples. (Previous posts: #1-2, #3 , #4.) This issue is simple but profound, and its prevalence is, I’ll argue, tied to more fundamental problems with how we do science. The mistake: drawing conclusions from … Continue reading Comments on “Small Samples” — “Ten common statistical mistakes…” #5

Continuing our series — see here for Part 1, and Part 2 — let’s look at Makin and Orban de Xivry’s Statistical Mistake #4: Spurious Correlations. This one is easy to understand, though nonetheless common. The authors refer to situations like the one illustrated in their Figure 2, shown below, in which the correlation calculated … Continue reading Comments on “Ten common statistical mistakes…”: #4

Continuing from the first post in this series, let’s look at Makin and Orban de Xivry’s Statistical Mistake #3: Inflating the units of analysis. The issue: What is N? In other words, how many independent data points are there, for whatever statistical analysis one wants to do? N is often mistakenly made larger than it … Continue reading Comments on “Ten common statistical mistakes…”: #3

The steady stream of scientific articles with irreproducible results, shaky conclusions, and poor reasoning [1] is, thankfully, accompanied by attempts to do something about it. A few months ago, Tamar Makin and Jean-Jacques Orban de Xivry published an excellent short article called “Ten common statistical mistakes to watch out for when writing or reviewing a … Continue reading Comments on “Ten common statistical mistakes…”: #1 and #2