The Beta distribution is a Probability distribution that has support over the interval $[0, 1]$. It's most commonly used to express degree of belief in the value of a probability term.

Some learnings while training myself in statistics.

Distributions:

• Probability distribution
• Dirichlet Process
• Dirichlet Distribution
• Hidden Markov Model
• Estimating a multivariate Gaussian's parameters by gradient descent
• Gaussians come from processes that are additive

Statistical Estimation:

• Fermi estimation and Bayesian priors
• When is your statistical model right vs. good enough
• Maximum score estimator is used to maximize classification true positives and negatives

Papers that I'm writing:

• Hierarchical Bayesian models for high throughput biological measurement

Dealing with data:

• Multiple imputation is better than imputing single values

Probabilistic Programming:

• Anatomy of a probabilistic programming framework
• PROBPROG2020 conference

Probability distribution can come in what I think of as "pre-configured" or "raw" states.

An example is a Gaussian. Without any configurations, it's got an infinite set of possible $\mu$ and $\sigma$ values. With a configuration, it has one $\mu$ and one $\sigma$.

Another example is the Beta distribution. Without any configurations, it's got an infinite set of possible $\alpha$ and $\beta$ parameter values. With a configuration, it has one $\alpha$ and one $\beta$.