The origin of statistics dates back to 17th-century Europe, beginning with the development of probability theory to calculate gambling odds

 The origin of statistics dates back to 17th-century Europe, beginning with the development of probability theory to calculate gambling odds. Thinkers like Pascal and Fermat laid the groundwork by attempting to express chance mathematically. This foundation later extended to applications in astronomy and population data, eventually evolving into modern statistics.

Fisherian statistics is a method that tests the significance of results by setting a null hypothesis and evaluating p-values. It introduced tools like analysis of variance (ANOVA) and maximum likelihood estimation, forming the basis of experimental design. It aims to show non-random patterns rather than proving truth.
Bayesian statistics, once deemed heretical for assigning probabilities to hypotheses, has recently gained renewed attention in fields like AI and medicine where uncertainty matters. By combining prior beliefs with data to calculate posterior probabilities, it enables rational decisions that surpass mere intuition.

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