Bayesian vs Frequentist statistics

Bayesian and Frequentist statistics are two approaches to understanding and making inferences from data. Bayesian statistics incorporates prior knowledge or beliefs, updating these as new data arrives to produce a "probability" of an event or hypothesis being true. It treats probability as a measure of certainty. Frequentist statistics, on the other hand, relies solely on data from experiments or observations, interpreting probability as the long-run frequency of an event over many repetitions. It evaluates hypotheses without prior beliefs, focusing on the likelihood of observing data assuming a hypothesis is true. Both methods inform decisions but differ in their foundational philosophy and interpretation.