---

Statistik II

Learning objectives

• knowledge of basic inferential methods, ability to describe and to apply them
• ability to interpret the methods' results
• ability to recognize and to justify which method is to apply in which situation

Contents

• calculus of probability (particularly Laplace probability, conditional probability, law of total probability, Bayes' theorem, stochastic independence, basic combinatorics)
• random variables (particularly discrete and continuous random variables, density and cumulative density, expectation, variance, quantiles; common, conditional, and marginal density of multivariate random variables, covariance and correlation, stochastic independence)
• probability distributions (particularly popular discrete and continuous distributions as the Binomial, hypergeometric, Poisson, geometric, uniform distribution, normal, t, and chi-squared distribution)
• estimation (particularly concept of an estimator, point and interval estimation)
• statistical hypothesis testing (particularly concept of a statistical test, selected tests on the expected value, test of a proportion, chi-squared test of independence)

Prerequisites

There are no formal prerequisites for participation in the course. However, knowledge of statistics and mathematics at bachelor level is desirable.

Lecture and exercise documents

Script, exercises, sample solutions as well as a collection of formulas are available for download in Stud.IP in the respective semester. Examinations with sample solutions from previous semesters can be found at the end of this page.

Scope and evaluation

• lecture and exercise each 2 WCH
• written exam
• 5 credit points

Dates

Lecture and exercise dates are announced via Stud.IP. Examination dates can be found on the website of the examination office.

Downloads

Up