The hottest Bayesian Substack posts right now

The Monty Hall problem has a new twist, focusing on a valuable goat instead of a car. In this version, knowing which goat is valuable affects your choice.
Using Bayes' theorem can help calculate the probabilities in this variation. After a goat is revealed, you can reassess your chances to make a better decision.
The essential lesson is to update your beliefs with new information. Recognizing how new clues impact your choices is key to making smarter decisions.

Probability and statistics differ in given information and desired outcomes
Statistical analysis involves hypothesis testing, parameter estimation, and confidence intervals
Bayesian statistics combines prior beliefs with evidence to reach posterior probabilities

Estimating values in multiple dimensions can be more accurate by making them slightly smaller towards zero.
Using a Bayesian prior of zero in analysis can be counterproductive and arbitrary.
Consider using realistic Bayesian priors, like room temperature, for more reasonable estimates.

Probability is a number that quantitatively measures the likelihood of events, always between 0 and 1.
Probability is a well-defined mathematical concept, separate from how probabilities are assigned.
The frequentist and Bayesian schools of thought differ in how they assign probabilities, but each has its own advantages in different situations.

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