Bayesian Inference
Bayesian inference is a method of statistical reasoning that updates our beliefs about a situation as we gather new evidence. It combines prior knowledge (what we already know) with new data to form a revised understanding. Imagine you have a hypothesis, like "It might rain today." If you check the weather forecast and see it predicts rain, you adjust your belief, weighing that new information against what you knew before. This process allows for more nuanced and informed decision-making, as it continually refines understanding based on incoming information.
Additional Insights
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Bayesian inference is a method of statistical reasoning that updates our beliefs about the likelihood of a hypothesis based on new evidence. It combines prior knowledge (our existing beliefs) with new data to produce an updated belief, known as the posterior. This process involves using Bayes' theorem, which mathematically relates the prior, the likelihood of observing the new evidence given the hypothesis, and the overall probability of the evidence. Essentially, it helps us refine our predictions and improve decision-making by systematically incorporating new information as it becomes available.