Parameter Estimation - The PDF, CDF and Quantile Function

April 14, 2015 by Will Kurt

Discover the fundamental of Bayesian Parameter estimation. Learn to use the Probability Density Function, Cumulative Distribution Function and Quantile Function to estimate unknown values in our data.

Expectation and Variance from High School to Grad School

April 07, 2015 by Will Kurt

Many people find the ideas of Expectation and Variance confusing. In part this is because the way we view these concepts changes as our understanding grows in sophistication. In this post we'll look at the way these definitions change from their basic High School intro to the view of Rigorous Probability Theory.

Working with Probability Distributions

March 31, 2015 by Will Kurt

Learn about Discrete and Continuous probability distributions as well as the types of questions that they can both answers. This post also discusses the relationship between the Binomial and Beta distributions.

Monte Carlo Simulations in R

March 24, 2015 by Will Kurt

Monte Carlo simulations are very fun to write and can be incredibly useful for solving ticky math problems. In this post we explore how to write six very useful Monte Carlo simulations in R to get you thinking about how to use them on your own.

Han Solo and Bayesian Priors

March 17, 2015 by Will Kurt

There is an iconic probability problem in The Empire Strikes Back! Han Solo is told that navigating an asteroid field is extremely unlikely to be successful. However not only does he navigate the asteroid field successfully, but we know he will. Learn how we can use Bayesian Priors to reconcile C3POs frequentist views on probability with our natural reasoning.

One in a Million and e

March 10, 2015 by Will Kurt

Euler's number (the mathematical constant e) shows up in a variety of unexpected places. One of them is in Probability. A common way of expressing probabilities is to say "there's a 1 in a million chance!". In this post we find out how that way of viewing probabilities eventually leads us to Euler's number.

Understanding Variance, Covariance, and Correlation

March 03, 2015 by Will Kurt

An explanation of Variance, Covariance and Correlation in rigorous yet clear terms providing a more general and intuitive look at these essential concepts.

Random Variables and Expectation with Robots and Stuff!

February 24, 2015 by Will Kurt

In this post we look at Expectation and Variance in simple terms, but through a more sophistcated lens. It turns out that "advanced" definitions of these terms are also easier to understand and work with.