Bayesian statistics the fun way

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Part 1. Introduction to probability. Bayesian thinking and everyday reasoning

Measuring uncertainty

The logic of uncertainty

Creating a binomial probability distribution

The beta distribution

Part 2. Bayesian probability and prior probabilities. Conditional probability

Bayes' theorem with LEGO

The prior, likelihood, and posterior of Bayes' theorem

Bayesian priors and working with probability distributions

Part 3. Parameter estimation. Introduction to averaging and parameter estimation

Measuring the spread of our data

The normal distribution

Tools of parameter estimation : the PDF, CDF, and Quantile function

Parameter estimation with prior probabilities

Part 4. Hypothesis testing: the heart of statistics. From parameter estimation to hypothesis testing : building a Bayesian A/B test

Introduction to the Bayes factor and posterior odds : the competition of ideas

Bayesian reasoning in the twilight zone

When data doesn't convince you

From hypothesis testing to parameter estimation

Appendix A: A quick introduction to R

Appendix B: Enough calculus to get by