Dream Cheating Scandal - Explaining All the Math Simply

Dive into a comprehensive 26-minute video analysis of the mathematical aspects surrounding the Dream cheating scandal in Minecraft speedrunning. Explore concepts like binomial distribution, bias corrections, and statistical tools used by both the moderation team and the hired astrophysicist. Learn about probability, statistics, and coding while examining the controversy. Follow along as the video breaks down complex math into understandable explanations, covering topics such as stopping criterion, stream selection bias, runner selection bias, and p-hacking. Gain insights into the mathematical arguments presented by both sides of the debate, including criticisms and potential mistakes. Suitable for those interested in gaming controversies, statistics, or applied mathematics in real-world scenarios.

Disclaimer.
Background of the drama.
Binomial distribution.
Applying binomial distribution.
Bias 1: Stopping criterion.
Bias 2: Stream selection bias.
Bias 3: Runner selection bias.
Bias 4: p-hacking.
Mod team math summary.
Main criticism from astrophysicist.
Minor criticisms from astrophysicist.
Blatant mistake of astrophysicist.
Outro and endcard stuff.
: p-values mean getting AT LEAST as lucky as these success rates, not just as lucky..
: The streams aren't exactly independent, so this is not an exact answer, but it works as an overestimate nonetheless because they are positively correlated; if you are not convinced, you can also consider the Bonferroni correction, which is very close to this..
: I said 1.19 * 10^(-12), but the figure shown on screen is correct: 1.19*10^(-11)..
: 1000 is the UPPER BOUND, not an estimation.
: This is based on the faulty assumption that all speedrun attempts are streamed..
: The astrophysicist's 1 in 6300 is somewhat close to the chance of 18 heads in a row, or 19 of heads or tails in a row, so maybe some coding mistakes, or that he is exceptionally lucky in obtaining so many runs of 20 heads in his simulation..