# Introduction to Bayesian Statistics

Bayes' Theorem and Bayesian statistics from scratch - a beginner's guide.
New
Rating: 4.7 out of 5 (33 ratings)
728 students
Introduction to Bayesian Statistics
New
Rating: 4.7 out of 5 (33 ratings)
728 students
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.

Who this course is for:
• 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.
Course content
4 sections • 14 lectures • 1h 18m total length
• Introduction
01:13
• Bayesian vs Frequentist models of probability
08:34
• Conditional Probability Intro
03:29
• Conditional Probability on Venn Diagrams
07:01
• Conditional Probability on Tree Diagrams
04:13
• Tree Diagram Example Question
04:37
• Conditional Probability and Normal Distributions
04:01
• Counter Intuitive Results with the Normal Distribution
08:20
• Developing Bayes' Theorem part 1
07:12
• Developing Bayes' Theorem part 2
07:47
• Thomas Bayes' Puzzle
05:36
• A Bayesian Solution to the Puzzle
06:50
• Simulating a Solution
09:28
• Congratulations!
00:19

Instructor
Mathematics Teacher

After finishing my studies at Oxford University I worked for a year in India before moving to London, which is where I have been ever since.

I have taught mathematics in some of the best performing schools in the country for over 10 years, where I have taught all levels of school maths, including GCSE, A-Level, Further Maths and Oxbridge entrance paper preparation.

Alongside this I have worked with businesses to train their staff in mathematical skills, such as statistics, data analysis and mathematical software packages.

Away from my work I love music and long-distance cycling, and recently cycled from London to Istanbul.