Tutorial 10: Bayesian Inference: Part 3

In this video, we apply Bayesian Inference to the coin toss problem. We revise in practice the concepts of Bernoulli and Binomial distributions and how they apply to our context. In the following video, we calculate the likelihood, primarily relying on the binomial distribution. This framework might seem basic, but it works much as a guide for more complex problems.

[bennywhite]

I appreciate the philosophical underpinnings of Bayesian thinking.

[williamjackson]

It's an extremely powerful tool that allows us to incorporate prior knowledge into our models.

[peterrodriguez]

I think it's intellectually stimulating and a useful addition to my analytical toolkit

[carolynhoward]

I'm astounded by how well it handles complex problems.

[amandabuckler]

I love how it accounts for uncertainty in a systematic way.

[judygray]

Bayesian models provide clear and interpretable results.

[amandawilliams]

It's a versatile approach that can be used in a variety of fields

[arthurchatman]

Bayesian Inference enriches data analysis with logic and intuition.