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DataCamp

Fundamentals of Bayesian Data Analysis in R

via DataCamp

Overview

Learn what Bayesian data analysis is, how it works, and why it is a useful tool to have in your data science toolbox.

Bayesian data analysis is an approach to statistical modeling and machine learning that is becoming more and more popular. It provides a uniform framework to build problem specific models that can be used for both statistical inference and for prediction. This course will introduce you to Bayesian data analysis: What it is, how it works, and why it is a useful tool to have in your data science toolbox.

Syllabus

What is Bayesian Data Analysis?
-This chapter will introduce you to Bayesian data analysis and give you a feel for how it works.

How does Bayesian inference work?
-In this chapter we will take a detailed look at the foundations of Bayesian inference.

Why use Bayesian Data Analysis?
-This chapter will show you four reasons why Bayesian data analysis is a useful tool to have in your data science tool belt.

Bayesian inference with Bayes' theorem
-Learn what Bayes theorem is all about and how to use it for statistical inference.

More parameters, more data, and more Bayes
-Learn about using the Normal distribution to analyze continuous data and try out a tool for practical Bayesian analysis in R.

Taught by

Rasmus Bååth

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