The science of collecting, analyzing, and interpreting data to draw inferences about populations from samples.
inference:: estimating population parameters from sample data
regression models relationships between variables, predicting outcomes
hypothesis testing evaluates evidence for or against a claim using p-values and significance
Bayesian statistics updates beliefs via Bayes theorem from probability
maximum likelihood estimation finds parameters that best explain observed data
central limit theorem:: sample means converge to a normal distribution regardless of source
Foundation of machine learning, experimental science, and decision-making
Related:: probability, linear algebra, optimization, information theory, game theory