6PAS1 Probabilty and Statistics 1, winter semester 2024/2025
A BRIEF SYNOPSIS
(Each class lasted approximately 1.5 hours if not specified otherwise; tutorials
were running separately)
Direct product of sample spaces. Examples of calculation of probabilities.
Class 10 December 2, 2024
Joint mass function, joint distribution function. Independent random
variables. If \(X\) and \(Y\) are indepenent random variables, then
\(E[XY] = E[X]E[Y]\). Covariance and correlation.
Class 11 December 9, 2024
Properties of correlation. Independent random variables are uncorrelated, but
not vice versa.
Datasets and their graphical representations.
Sample mean, sample variance, sample correlation (unbiased estimators).
Correlation is not causation.
Class 12 December 16, 2024
Statistical model, linear statistical model (linear regression), method of least
squares. Hypothesis testing, test statistic, null and alternative hypothesis,
\(p\)-value, type I and type II error.
Winter semesters from 2017/2018 till 2019/2020:
Created: Sun Sep 21 2025
Last modified: Tue Nov 25 2025 12:59:51 CET