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Introduction To Bayesian Statistics
Last updated 8/2020
MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz
Language: English | Size: 933.92 MB | Duration: 1h 19m
Bayes' Theorem and Bayesian statistics from scratch - a beginner's guide.
What you'll learn
Bayes' Theorem
Bayesian statistics
Conditional probability
An understanding of subjective approaches to probability
Using Venn and Tree diagrams to model probability problems
Requirements
An understanding of probability basics.
Description
Bayesian statistics is used in many different areas, from machine learning, to data analysis, to sports betting and more. It's even been used by bounty hunters to track down shipwrecks full of gold!This beginner's course introduces Bayesian statistics from scratch. It is appropriate both for those just beginning their adventures in Bayesian statistics as well as those with experience who want to understand it more deeply.We begin by figuring out what probability even means, in order to distinguish the Bayesian approach from the Frequentist approach.Next we look at conditional probability, and derive what we call the "Baby Bayes' Theorem", and then apply this to a number of scenarios, including Venn diagram, tree diagram and normal distribution questions.We then derive Bayes' Theorem itself with the use of two very famous counter-intuitive examples.We then finish by looking at the puzzle that Thomas Bayes' posed more than 250 years ago, and see how Bayes' Theorem, along with a little calculus, can solve it for us.
Overview
Section 1: Introduction
Lecture 1 Introduction
Section 2: What is probability?
Lecture 2 Bayesian vs Frequentist models of probability
Section 3: Conditional Probability
Lecture 3 Conditional Probability Intro
Lecture 4 Conditional Probability on Venn Diagrams
Lecture 5 Conditional Probability on Tree Diagrams
Lecture 6 Tree Diagram Example Question
Lecture 7 Conditional Probability and Normal Distributions
Lecture 8 Counter Intuitive Results with the Normal Distribution
Section 4: Bayes' Theorem
Lecture 9 Developing Bayes' Theorem part 1
Lecture 10 Developing Bayes' Theorem part 2
Lecture 11 Thomas Bayes' Puzzle
Lecture 12 A Bayesian Solution to the Puzzle
Lecture 13 Simulating a Solution
Lecture 14 Congratulations!
People who want to understand Bayes' Theorem intuitively and deeply.,People interested in probability.,Data scientists looking to develop their understanding of probability theory.,Students interested in deepening their understanding of probability.
Homepage
https://www.udemy.com/course/introduction-to-bayesian-statistics/
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