@jadeneoca: Definitions: Power Law: A distribution where a small minority of outcomes drive the majority of results. Put simply, think of the 80/20 rule, but more extreme. Correlation: When two variables tend to move together, but this does not necessarily indicate that one is caused by the other. St. Petersburg Paradox: A hypothetical game that proves that solely looking at expected value is not always the correct way of making decisions, especially when potential outcomes are extreme or theoretically infinite. Regression to the mean: When extreme outcomes are typically followed by more average ones, not because of worsening or improving performance, but just because average outcomes occur more often Law of large numbers: The more times you repeat something, the more the average converges to its true probability or expected value. Availability heuristic: We judge probability based on how easily an example comes to mind, not how often it actually happens. Base rate fallacy: People ignore overall probabilities when looking at a specific case. For example, if there's a 1% chance you get a disease and a test is 99% accurate, if you test positive, you might think that there's a 99% chance you have the disease, but there's actually only a 50% chance you have the disease. Kelly criterion: A formula that tells you how much of your resources you should risk based on the payoff and probability of success Texas sharpshooter fallacy: Drawing the target around bullet holes that have already been shot, essentially going backwards and finding patterns that were not actually predicted up front Simpson’s Paradox: A trend that appears in two separate groups can completely reverse or disappear when those groups are combined.

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Saturday 27 June 2026 17:03:49 GMT