Bayesian Priors for Parameter Estimation
We've already looked at Bayesian Parameter Estimation, now we'll learn how to use Prior Probabilities in our Parameter Estimation to get better results.
Read MoreWe've already looked at Bayesian Parameter Estimation, now we'll learn how to use Prior Probabilities in our Parameter Estimation to get better results.
Read MoreDiscover 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.
Read MoreMany 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.
Read MoreLearn 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.
Read MoreMonte 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.
Read MoreThere 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.
Read MoreEuler'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.
Read MoreAn explanation of Variance, Covariance and Correlation in rigorous yet clear terms providing a more general and intuitive look at these essential concepts.
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