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Episode 33: Probability (and Tom's new book)

The Studies Show

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Exploration of Inferential and Sampling Probability with Thomas Simpson

The insight highlights the distinction between inferential probability and sampling probability, showcasing how Bernoulli mistakenly assumed them to be the same. It delves into Thomas Simpson's contribution as the first statistician to provide advice to scientists on aggregating data for more accurate results by emphasizing the importance of taking multiple measurements. Simpson's work on inference, rather than sampling probabilities, laid the foundation for modern statistical analysis. Furthermore, the interaction of Simpson's work with the Reverend Thomas Bayes underscores the significance of their contributions to shaping modern probability theory.

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