课程: Probability Foundations for Data Science

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Frequentist vs. Bayesian probability

Frequentist vs. Bayesian probability

课程: Probability Foundations for Data Science

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Frequentist vs. Bayesian probability

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- [Instructor] As mentioned earlier, there are two main approaches to probability, frequentist and Bayesian. Let's review the differences between these two probability methodologies. First, let's look at how the foundations of these two methodologies differ. The frequentist approach believes probability is objective and is based on the idea that probabilities are derived from the frequency of repeated experiments and trials over the long run. The Bayesian approach believes probability is subjective and is interpreted as a degree of certainty about an event that is updated when new information becomes available. The frequentist approach believes hypotheses are fixed and the data is considered random to provide consistent results. The Bayesian approach believes both hypotheses and data are random where hypotheses are updated with prior beliefs regarding the data. Next, let's explore how these two approaches deal with prior information. The frequentist approach does not incorporate any…

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