Advantages of Bayes’ Theorem over Deterministic Statistics

Bayes’ theorem is a statistical method used to update the probability of an event occurring after considering new evidence. Bayes’ theorem is used in various fields, including machine learning, natural language processing, and data analysis.

There are several advantages to using Bayes’ theorem over deterministic statistics:

Incorporation of prior knowledge

In Bayesian statistics, prior knowledge or beliefs about the probability of an event can be incorporated into the analysis. This is in contrast to deterministic statistics, which only consider the current data and do not consider any prior knowledge.

Example

Imagine that we are trying to predict the reliability of a particular software system. We have data on the reliability of similar systems, but we also have some prior knowledge about the distribution of reliability values based on our experience with comparable systems. In a Bayesian analysis, we could use this prior knowledge to inform our predictions about the system’s reliability.