Introduction to Bayesian Statistics

Unlock the power of Bayesian Statistics: A Beginner's Guide

Discover the fascinating world of Bayesian statistics, a powerful tool used in diverse fields like machine learning, data analysis, and even sports betting! You might be surprised to learn it's also been employed in real-world scenarios, such as by bounty hunters tracking lost shipwrecks.

This comprehensive course introduces Bayesian statistics from the ground up, making it perfect for both those new to the concepts and experienced individuals seeking a deeper understanding.

Here's what you'll learn:

• Understanding Probability: We start with the fundamental question: What is probability? We'll explore how the Bayesian approach differs from the traditional Frequentist approach, laying a solid foundation for your journey.
• Conditional Probability & Baby Bayes' Theorem: Dive into conditional probability and derive the essential "Baby Bayes' Theorem." We'll then apply this to solve problems using visual tools like Venn diagrams and tree diagrams, as well as incorporating the normal distribution.
• Deriving Bayes' Theorem: Explore the core of Bayesian statistics by deriving Bayes' Theorem itself. We'll use two compelling, counter-intuitive examples to make the derivation clear and intuitive.
• The Thomas Bayes Puzzle: Conclude the course by tackling the original puzzle posed by Thomas Bayes over 250 years ago. You'll see how Bayes' Theorem, combined with basic calculus, provides a powerful solution.

Whether you're just starting to explore Bayesian statistics or aiming to refine your existing knowledge, this course will equip you with the skills to apply this versatile statistical method.