Introduction to Bayesian statistics with explained examples. Learn about the prior, the likelihood, the posterior, the predictive distributions. Discover how to make Bayesian inferences about quantities of …

Jan 24, 2025 · This article is a concise look at five real-world applications that illustrate the breadth of Bayesian techniques.

Jul 26, 2025 · Bayesian statistics uses three key parts: the likelihood function, prior belief, and posterior belief. These help handle yes/no outcomes and let us update our beliefs as we get new information.

Materials and examples from the course are discussed more extensively and extra examples and exer-cises are provided.

On this webpage, we illustrate some of the concepts described in Introduction to Bayesian Statistics. The false-positive rate for an HIV test is 7% and the false-negative rate is 1%. If 0.148% of the …

Let's take a look at a simple example in an attempt to emphasize the difference. A traffic control engineer believes that the cars passing through a particular intersection arrive at a mean rate λ equal …

Lecture 20 | Bayesian analysis Our treatment of parameter estimation thus far has assumed that is an unknown but non-random quantity|it is some xed parameter describing the true distribution of data, …

Dec 29, 2025 · In this beginner’s guide on Bayesian Statistics, I’ve tried to explain the concepts in a simplistic manner with examples. Prior knowledge of basic probability & statistics is desirable. You …

This article has been written to help you understand the "philosophy" of the Bayesian approach, how it compares to the traditional/classical frequentist approach to statistics and the potential applications …

We’ll run a linear regression using frequentist and Bayesian methods. We use the dataset as a sample dataset. The data contains the hourly and daily count of rentalbikes between years 2011 and 2012 in …