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

Physical explanation and prior work

• Several comments reference a video explaining that “precession” (wobble and off‑axis spin) makes coins spend more time on one side, producing a same‑side bias.
• A 2007 theoretical paper predicting ~51% same‑side probability is cited; the new study with ~350k flips is seen as an empirical test of that model.
• Reported aggregate estimate: Pr(same side) ≈ 0.508 with a narrow credible interval.

Statistics and significance

• Some want stronger or clearer Bayesian explanations for lay audiences; others note the paper itself uses Bayesian methods.
• One commenter stresses that the effect is tiny in practice (e.g., ~51 vs 49 same‑side outcomes per 100 flips), so exploitable advantage is extremely small.

Methodology and validity debates

• Major thread: whether the flips in the study are “real” or “proper” coin tosses.
  • Critics point to videos showing low‑height, low‑RPM flips and argue that most people, especially when decisions matter, flip higher and faster.
  • Others respond that the study’s goal is to measure how typical humans actually flip in practice, not an idealized mechanical toss.
• Concerns include:
  • Only ~48 flippers generating a huge number of flips each, leading to questions about representativeness and learning effects.
  • Participants also being co‑authors, which some see as potential bias.
• A researcher replies:
  • Videos look slow because of 30fps webcams; coins often spin faster than visible.
  • Flippers were instructed to flip “as if settling a bet” and to ensure at least one full flip.
  • Bias generally decreased over time, suggesting practice reduces wobble rather than deliberate gaming.
  • Outlier‑exclusion and sensitivity analyses still show same‑side bias; raw data and scripts are publicly available.

Human skill, bias heterogeneity, and cheating

• Data reportedly show large variation between individuals: some near‑fair, some strongly biased, consistent with a continuum of skill/technique.
• Several comments note magicians and practiced individuals can strongly control outcomes via precession or by never actually flipping the coin (only spinning it in plane).
• This is framed as evidence that coin flips are deterministic physics plus human inconsistency, not intrinsically random.

Fair coins vs fair flips

• Multiple comments distinguish:
  • A coin biased toward heads/tails (lands that side more often regardless of starting orientation).
  • A same‑side bias (more likely to land on whatever side it started).
• Some initially misattribute the effect to inherently unfair coins; others clarify that randomizing starting orientation via a RNG would cancel a pure heads/tails bias but not a same‑side bias.

Practical implications and “fixes”

• Several discuss whether to bet on the effect; consensus is that the edge is too small and protocol‑sensitive to be practically useful.
• Standard debiasing technique is mentioned: von Neumann “whitening” by using pairs of flips (HT vs TH) to extract fair bits from a biased but consistent coin.
• One commenter notes this relies on independent flips; if flips are correlated or coins are maliciously manipulated, no procedure can fully guarantee fairness.

Ig Nobel and perception of the work

• The study’s Ig Nobel Prize in probability is noted.
• Some see Ig Nobels as mocking “legitimate” research; others emphasize the stated goal is to highlight surprising work that makes people “laugh, then think.”

Broader reflections and tangents

• Commenters debate what counts as a “normal” coin flip and whether we should replace tossing with shaking coins in a box or using machines.
• A tongue‑in‑cheek ethics question asks whether revealing bias in coin flips might worsen human disputes.
• There are playful digressions into simulation arguments, quantum mechanics, and “conservation of reality,” generally treated as speculative or humorous rather than serious explanations.