fbartos
Joined 4 years ago
Joined 4 years ago
The main difference from the original version is that we now document a decrease in the same-side bias over time. Meaning the more people flip, the less biased they are. We guess that it's a practice effect -- they might be getting better at coin flipping over time.
(I'm the main author of the paper)
Yes, training the most wobbly flippers sounds like a very interesting idea. It might indeed answer additional questions but it's not really something I wanna run more studies on :)
Wrt to the height, that naturaly varied among people and flips and we did not measure it.
Low RPM tosses: Most of the recordings are on crapy webcams with ~ 30FPS. The coin spin usually much faster than the sensor can record which results in often non-spinning-looking flips. Why did we take the videos in the first place? To check that everyone collected the data and to audit the results.
Building a flipping matching: The study is concerned with human coin flips. Diaconis, Holmes, and Montgomery's (DHM, 2007) paper theorize that the imperfection of human flips causes the same-side bias. Building a machine completely defeats the purpose of the experiment.
Many authors and wasted public funding: We did the experiment in our free time and we had no funding for the study = no money was wasted. Also, I don't understand why are so many people angry that students who contributed their free time and spent the whole day flipping coins with us were rewarded with co-authorship. The experiment would be impossible to do without them.
Improper tosses: Not everyone flips coin perfectly and some people are much worse at flipping than others. We instructed everyone to flip the coin as if they were to settle a bet and that the coin has to flip at least once (at least one flip would create bias for the opposite side). We find that for most people, the bias decreased over time which suggests that people might get better at flipping by practice = decrease the bias and it also discredits the theory that they learned how to be biased on purpose. From my own experience - I flipped coins more than 20,000 times and I have no clue how to bias it. Also, we did a couple of sensitivity analyses excluding outliers - the effect decreased a bit but we still found plentiful evidence for DHM.
If you doubt my stats background, you are more than welcome to re-analyze the data on your own. They are available on OSF: https://osf.io/mhvp7/ (including cleaning scripts etc).
Frantisek Bartos
Diaconis, P., Holmes, S., & Montgomery, R. (2007). Dynamical bias in the coin toss. SIAM Review, 49(2), 211-235. https://doi.org/10.1137/S0036144504446436
People were pressing one button for heads and another button for heads (which we deemend less error prone and less likely to be subcontiously influenced). The trick was that the next coin flip started the same side-up as the previous landed. Therefore there was no need to record the start (and we randomized the starting position of every 100th flip)
We also did some auditing of the video recordings (trying to decode the outcomes from the videos) and they showed quite consistent degree of bias as the original responses.
(I know that there are techniques for adding the wobble to the toss, but I didn't study them and I have no clue how to do them. I think it is safe to say you don't discover them intuitevelly.)
Also, I wish I had (any) budget to hire proffesional skilled tossers haha.
People flipping them however introduce bias due to the wobble of their tosses.