Fundamentals of Data Science Part I: Inference and Experiment

In Part I of this series we cover basic statistical inference and experimentation focusing on: basic statistics;derivation and review of key distributions and their relations;hypothesis testing including an in depth power analysis for the chi-squared statistic;experimentation including A/B tests stratification one- and two-factor experiments and an introduction to bandit algorithms; maximum likelihood;gradient descent;introduction to survival analysis and stochastic processes including empirical estimation of online survival and event processes.The theory is illustrated with simulations in Python throughout the text.