This course is inspired by the one written by my predecessor: Myriam Normand.
It is necessary to have prior knowledge in Probabilities. As such, it is advised to be proficient in
- random variables and usual distributions (normal, Bernoulli, etc.)
- expectation (variance, conditional expectation, etc.)
- convergence of random variables (law of large numbers, central limit theorem, etc.)
- probability distribution, cumulative distribution function, etc.
This course is designed to provide a quick introduction to stastical inference for data engineers. As such, it meets different educational objectives:
- learn how to design a statistical test
- evaluate the risks
SlidesIntroduction to Statistical Tests Tests of Conformity Tests of Homogeneity Paired Samples Tests Tests of Normality Tests of Independence