Frequentist statistics Samenvattingen, Aantekeningen en Examens

This document contains the lecture notes for all lectures of 0HV110, both for part 1 (by Chris Snijders) and part 2 (by Daniël Lakens). The notes are conveniently divided into weeks, and then ordered into the different lectures by the different teachers. Pro-tip: buy my 0HV110 bundle for a discount on the documents!

This document contains an overview of all statistical terms used in the 0HV110 course part 2 (by Daniël Lakens) including their definitions, and some extra explanation. Learning this summary gives a good preparation for the exam. It is ordered by week, and based on the provided video lectures. Furthermore, this document is useful for all students and scientists who want to gain better understanding in statistical concepts. Pro-tip: buy my 0HV110 bundle for a discount on the documents!

[R] Cheatsheet for the Statistics for Data Scientists course of the Premaster Data Science and Entrepreneurship.

Summary for the Statistics for Data Scientists course of the Premaster Data Science and Entrepreneurship.

Data Science Handbook containing the most relevant notions related to point estimation for the "Inferential Statistics" exam. You will be introduced to the notion of an estimator and to its properties in the context of normally distributed data. The text includes the steps, to be followed in R, useful for simulating the various properties of the mean and variance estimators as well as the analytical demonstrations of the mean, variance and standard error of the latter.

This Summary reflects the content of the course "Statistics for CSAI 2" of the bachelor track in Cognitive Science and Artificial Intelligence at Tilburg University. As this is a summary of an intermediate Statistics course, it is applicable to any other statistics course of this kind; not necessarily for CSAI. The content covered is the following: - Probability vs. Statistics (probability theory, bayesian vs. frequentist etc.) - Probability Distributions (normal, binomial, t, f, chi-square...