Statistics
A collection of introductory ideas in Statistics.
Content by idea can be found below.
Statistics
An introduction to outcomes, outcome spaces, events, probability, mutually exclusive events, exhaustive events, set laws, conditional probability, partitions of the outcome space, the addition law, the multiplication law (Bayes’ Theorem), and the law of total probability.
Estimators
An introduction to independent events, random variables, state spaces, countable sets, discrete random variables, probability mass functions, and expected value.
Confidence Intervals
An introduction to continuous random variables, probability density functions, cumulative density functions, expected value, variance, and standard deviation.
Prediction Intervals
An introduction to tail moments, Bernoulli random variables, binomial random variables, binomial shape, and geometric random variables.
Simple Linear Models
An introduction to negative binomial random variables, negative binomial shape, hypergeometric random variables, and Poisson random variables.
Thank you for reading to the end.