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You are here		ergodicity.net Mean absolute deviations for binomial random variables \| An Ergodic Walk
\|	\|	danieltakeshi.github.io The Expectation of the Minimum of IID Uniform Random Variables	6.1 parsecs away Travel
\|	\|	In my STAT 210A class, we frequently have to deal with the minimum of asequence of independent, identically distributed (IID) random variables. Thishappens b...	6.1 parsecs away Travel
\|	\|	geekyisawesome.blogspot.com Geeky is Awesome: Bernoulli vs Binomial vs Multinoulli vs Multinomial distributions	5.8 parsecs away Travel
\|	\|	Bernoulli distribution Say you are flipping a coin that has a probability of 0.4 of turning up heads and 0.6 of turning up tails. The simple...	5.8 parsecs away Travel
\|	\|	www.randomservices.org Beta-Bernoulli Process	4.4 parsecs away Travel
\|	\|	[AI summary] The text presents a comprehensive overview of the beta-Bernoulli process and its related statistical properties. Key concepts include: 1) The Bayesian estimator of the probability parameter $ p $ based on Bernoulli trials, which is $ rac{a + Y_n}{a + b + n} $, where $ a $ and $ b $ are parameters of the beta distribution. 2) The stochastic process $ s{Z} = rac{a + Y_n}{a + b + n} $, which is a martingale and central to the theory of the beta-Bernoulli process. 3) The distribution of the trial number of the $ k $th success, $ V_k $, which follows a beta-negative binomial distribution. 4) The mean and variance of $ V_k $, derived using conditional expectations. 5) The connection between the beta distribution and the negative binomial distributi...	4.4 parsecs away Travel
\|	\|	akosiorek.github.io Normalizing Flows	38.3 parsecs away Travel
\|		Machine learning is all about probability.To train a model, we typically tune its parameters to maximise the probability of the training dataset under the mo...	38.3 parsecs away Travel