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  3. Fundamentals of Bayesian Data Analysis in R
  • 1

    What is Bayesian Data Analysis?

    Free

    This chapter will introduce you to Bayesian data analysis and give you a feel for how it works.

  • 2

    How does Bayesian inference work?

    In this chapter we will take a detailed look at the foundations of Bayesian inference.

  • 3

    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.

  • 4

    Bayesian inference with Bayes' theorem

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

  • 5

    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.

Initializing

Exercise

Looking at samples from prop_model

Here again is the prop_model function which has been given the data from our zombie experiment where two out of 13 zombies got cured. In addition to producing a plot, prop_model also returns a large random sample from the posterior over the underlying proportion of success.

Instructions 1/3

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  • Assign the return value of prop_model to a variable called posterior and take a look at the first number of samples using the command head(posterior).