Fair coins tend to land on the side they started (2023)

The paper looks like it has a large sample size, but it actually has a sample size of only 48 testers/flippers. Some of the videos of those testers show very low, low-rpm coin tosses, we're talking only 1-2 flips. Where they also flipped thousands of times, presumably in the same way. So there is actually a very small sample size in the study (N = 48), where testers that don't flip properly (low rpm, low height, few coin rotations) can affect the results disproportionately.

Doesn't look like the study author backgrounds are particularly focused on statistics. I would presume with 48 authors (all but 3 of which flipped coins for the study), the role of some might have been more test subject than author. And isn't being the subject in your own study going to introduce some bias? Surely if you're trying to prove to yourself that the coins land on one side or another given some factor, you will learn the technique to do it, especially if you are doing a low-rpm, low flip. Based on the study results, some of the flippers appear to have learned this quite well.

If the flippers (authors) had been convinced of the opposite (fair coins tend to land on the opposite side from which they started) and done the same study, I bet they could have collected data and written a paper with the results proving that outcome.

> testers that don't flip properly

I think that's the point. It shows that people don't usually flip properly, leading to biased results.

There is a [video presentation of the paper](https://www.youtube.com/watch?v=-QjgvbvFoQA) which does a good job of explaining the inspiration for the study within the first few minutes.

It sounds like what they were intending to study is the actual variance that is introduced, on average, by imperfections in throws conducted by humans. Unless that's mistaken, it's a fair point to consider the n=48 here. Did they discover an average that can be generalized to humans or just to those 48?