t.BA.XXM7.STS.19HS (Stochastics and Statistics)
Module: Stochastics and Statistics
This information was generated on: 27 September 2021
No.
t.BA.XXM7.STS.19HS
Title
Stochastics and Statistics
Organised by
T IAMP
Credits
4

### Description

Version: 1.0 start 01 February 2019

#### Short description

The module introduces the terms and concepts of probability theory and statistics that are indispensable for a deeper understanding of many areas.

#### Module coordinator

Reif Monika (reif)

#### Learning objectives (competencies)

 Objectives Competences Taxonomy levels You can visualize data from a statistical point of view and calculate various statistical values. You can use statistics software to do this. F,M K3, K4 You know the basics of probability theory for the analytical description of random events. F,M K2, K3 You can use probability theory methods to analytically calculate probabilities and use them to evaluate dependent and independent events. F,M K3, K4 You understand the concept of random variables and the properties of probability density and distribution function. F,M K3, K4 You know the most important distributions and know how to calculate their parameters. F,M K2, K3 You know the laws of large numbers and the central limit theorem and their significance in statistical applications. F,M K2, K3 You know general methods for estimating parameters and can apply them. F,M K3, K4

#### Module contents

Descriptive Statistics
• Introduction of statistical software
• Representation of frequencies and distribution function
• Measures of central tendency and measures of variation
• Classified data
• Bivariate and multivariate data (optional)
• Correlation
Probability calculus
• Random events
• Concept of probability
• Probability models
• Stochastic independence
• Conditional probability
Distributions
• Random variable
• Density function
• Distribution function
• Discrete distributions
• Continuous distributions
• Parameters
• Limit theorems
Estimating and testing
• Point estimate (such as linear regression, maximum likelihood estimation, moment method)
• Interval estimation
• Hypothesis testing

#### Teaching materials

Lecture notes, exercise series

#### Supplementary literature

Teschl, G; Teschl,S.: Mathematik für Informatiker
Fahrmeir, L. et al: Statistik
Cramer, E.; Kamps, U.: Grundlagen der Wahrscheinlichkeitsrechnung und Statistik - Eine Einführung für Studierende der Informatik, der Ingenieur- und Wirtschaftswissenschaften

#### Teaching language

(X) German ( ) English

( ) Yes (X) No

Type 3a

#### Exams

 Description Type Form Scope Grade Weighting Graded assignments during teaching semester Exam or exercises written or oral max. 20% End-of-semester exam Exam written 90 min. graded min. 80%

#### Legal basis

The module description is part of the legal basis in addition to the general academic regulations. It is binding. During the first week of the semester a written and communicated supplement can specify the module description in more detail.
Course: Stochastik und Statistik - Praktikum
No.
t.BA.XXM7.STS.19HS.P
Title
Stochastik und Statistik - Praktikum

### Note

• No module description is available in the system for the cut-off date of 01 August 2099.
Course: Stochastik und Statistik - Vorlesung
No.
t.BA.XXM7.STS.19HS.V
Title
Stochastik und Statistik - Vorlesung

### Note

• No module description is available in the system for the cut-off date of 01 August 2099.