t.BA.XXM7.STS.19HS (Stochastics and Statistics) 
Module: Stochastics and Statistics
This information was generated on: 04 October 2024
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

Prerequisites

  

Teaching language

 (X) German ( ) English

Part of International Profile

 ( ) Yes (X) No

Module structure

 Type 3a
  For more details please click on this link: T_CL_Modulauspraegungen_SM2025

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%

Remarks

  

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.