Bayesian statistics

Bayesian statistics is a theory in the field of statistics based on the Bayesian interpretation of probability where probability expresses a degree of belief in an event. The degree of belief may be based on prior knowledge about the event, such as the results of previous experiments, or on personal beliefs about the event. This differs from a number of other interpretations of probability, such as the frequentist interpretation that views probability as the limit of the relative frequency of an event after many trials. Bayesian statistical methods use Bayes' theorem to compute and update probabilities after obtaining new data. Bayes' theorem describes the conditional probability of an event based on data as well as prior information or beliefs about the event or conditions related to the event. For example, in Bayesian inference, Bayes' theorem can be used to estimate the parameters of a probability distribution or statistical model. Since Bayesian statistics treats probability as a degree of belief, Bayes' theorem can directly assign a probability distribution that quantifies the belief to the parameter or set of parameters. Bayesian statistics is named after Thomas Bayes, who formulated a specific case of Bayes' theorem in a paper published in 1763. In several papers spanning from the late 18th to the early 19th centuries, Pierre-Simon Laplace developed the Bayesian interpretation of probability. Laplace used methods that would now be considered Bayesian to solve a number of statistical problems. Many Bayesian methods were developed by later authors, but the term was not commonly used to describe such methods until the 1950s. During much of the 20th century, Bayesian methods were viewed unfavorably by many statisticians due to philosophical and practical considerations. Many Bayesian methods required much computation to complete, and most methods that were widely used during the century were based on the frequentist interpretation. However, with the advent of powerful computers and new algorithms like Markov chain Monte Carlo, Bayesian methods have seen increasing use within statistics in the 21st century. (Wikipedia).

Bayesian vs frequentist statistics probability - part 1

This video provides an intuitive explanation of the difference between Bayesian and classical frequentist statistics. If you are interested in seeing more of the material, arranged into a playlist, please visit: https://www.youtube.com/playlist?list=PLFDbGp5YzjqXQ4oE4w9GVWdiokWB9gEpm Unfo

From playlist Bayesian statistics: a comprehensive course

What the Heck is Bayesian Stats ?? : Data Science Basics

What's all the hype about Bayesian statistics? My Patreon : https://www.patreon.com/user?u=49277905

From playlist Bayesian Statistics

Bayesian statistics syllabus

A description of the syllabus that will be covered in this course on Bayesian statistics. If you are interested in seeing more of the material, arranged into a playlist, please visit: https://www.youtube.com/playlist?list=PLFDbGp5YzjqXQ4oE4w9GVWdiokWB9gEpm Unfortunately, Ox Educ is no m

From playlist Bayesian statistics: a comprehensive course

What is a probability distribution?

An introduction to probability distributions - both discrete and continuous - via simple examples. If you are interested in seeing more of the material, arranged into a playlist, please visit: https://www.youtube.com/playlist?list=PLFDbGp5YzjqXQ4oE4w9GVWdiokWB9gEpm For more information

From playlist Bayesian statistics: a comprehensive course

Bayesian vs frequentist statistics

From playlist Bayesian statistics: a comprehensive course

Bayesian vs frequentist statistics probability - part 2

This video provides a short introduction to the similarities and differences between Bayesian and Frequentist views on probability. If you are interested in seeing more of the material, arranged into a playlist, please visit: https://www.youtube.com/playlist?list=PLFDbGp5YzjqXQ4oE4w9GVWdi

From playlist Bayesian statistics: a comprehensive course

36 - Population mean test score - normal prior and likelihood

This video provides an example of Bayesian inference for the case of a normal prior and normal likelihood. If you are interested in seeing more of the material, arranged into a playlist, please visit: https://www.youtube.com/playlist?list=PLFDbGp5YzjqXQ4oE4w9GVWdiokWB9gEpm Unfortunately,

From playlist Bayesian statistics: a comprehensive course

Bayesian Linear Regression : Data Science Concepts

The crazy link between Bayes Theorem, Linear Regression, LASSO, and Ridge! LASSO Video : https://www.youtube.com/watch?v=jbwSCwoT51M Ridge Video : https://www.youtube.com/watch?v=5asL5Eq2x0A Intro to Bayesian Stats Video : https://www.youtube.com/watch?v=-1dYY43DRMA My Patreon : https:

From playlist Bayesian Statistics

5 - Bayes' rule in statistics

An introduction to the use of Bayes' rule in statistics. If you are interested in seeing more of the material, arranged into a playlist, please visit: https://www.youtube.com/playlist?list=PLFDbGp5YzjqXQ4oE4w9GVWdiokWB9gEpm Unfortunately, Ox Educ is no more. Don't fret however as a whol

From playlist Bayesian statistics: a comprehensive course

Bayesian or Frequentist: What Does It Mean? (Chelsea Parlett) - KNN Ep. 55

Chelsea is a full time faculty member teaching undergraduate Data Science and Computer Science, and earned her PhD this year in Computational and Data Science. She also does casual statistical consulting at the Chatistician which aims to empower people to do their own statistics well. In h

From playlist Ken's Nearest Neighbors Podcast

Supercharging Decision Making with Bayes

Bayesian Decision Theory is a fundamental statistical approach to the problem of pattern classification. It is considered as the ideal pattern classifier and often used as the benchmark for other algorithms because its decision rule automatically minimizes its loss function. PUBLICATION P

From playlist Machine Learning

SDS 507: Bayesian Statistics — with Rob Trangucci

Rob Trangucci joins us to discuss his work and study in Bayesian statistics and how he applies it to real-world problems. In this episode you will learn: • Getting Rob on the show [5:43] • Stan [7:08] • Gradients [15:50] • What is Bayesian statistics? [20:44] • Multi-modal deep learning [

From playlist Super Data Science Podcast

Statistics in Machine Learning: Bayesian vs. Frequentist

Statistics in Machine Learning: Bayesian vs. Frequentist Teacher: Dr. Michael Pyrcz For more webinars & events please checkout: http://daytum.io/events Website: https://www.daytum.io/ Twitter: https://twitter.com/daytum_io?lang=en LinkedIn: https://www.linkedin.com/company/35593451 Data

From playlist daytum Free Webinar Series

Bayesian Statistics: An Introduction

See all my videos here: http://www.zstatistics.com/videos/ 0:00 Introduction 2:25 Frequentist vs Bayesian 5:55 Bayes Theorum 10:45 Visual Example 15:05 Bayesian Inference for a Normal Mean 24:30 Conjugate priors 32:55 Credible Intervals

From playlist Statistical Inference (7 videos)

Statistical Rethinking Winter 2019 Lecture 01

Lecture 01 of the Dec 2018 through March 2019 edition of Statistical Rethinking: A Bayesian Course with R and Stan.

From playlist Statistical Rethinking Winter 2019

Bayes Billiards with Tom Crawford

Bayes' Theorem allows us to assign a probability to an unknown fact. Thomas Bayes himself described an experiment with a billiard table, which is brilliantly explained by Hannah Fry and Matt Parker here https://www.youtube.com/watch?v=7GgLSnQ48os Brian Cox and David Spiegelhalter did a 1

From playlist Collaborations

Statistical Rethinking Fall 2017 - week01 lecture01

Week 01, lecture 01 for Statistical Rethinking: A Bayesian Course with Examples in R and Stan, taught at MPI-EVA in Fall 2017. This lecture covers Chapters 1 and 2. Slides are available here: https://speakerdeck.com/rmcelreath Additional information on textbook and R package here: http

From playlist Statistical Rethinking Fall 2017

What is a conditional probability?

An introduction to the concept of conditional probabilities via a simple 2 dimensional discrete example. If you are interested in seeing more of the material, arranged into a playlist, please visit: https://www.youtube.com/playlist?list=PLFDbGp5YzjqXQ4oE4w9GVWdiokWB9gEpm For more inform

From playlist Bayesian statistics: a comprehensive course

Bayesian statistics

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