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This entry is from Winter semester 2019/20 and might be obsolete. You can find a current equivalent here.

Elementary Stochastics (for teacher students)
(dt. Elementare Stochastik (Lehramt))

Level, degree of commitment Advanced module, depends on importing study program
Forms of teaching and learning,
workload		 Lecture (4 SWS), recitation class (2 SWS),
270 hours (attendance in den Lehrveranstaltungen 90 h, 150 h preparation and follow-up inklusive Studienleistungen, 30 h Vorbereitung and Ablegen von Prüfungsleistungen)
Credit points,
formal requirements		 9 CP
Course requirement(s): Successful completion of at least 50% of the weekly exercises as well as at least 1-3 presentations of the tasks
Examination type: Written examination (90-120 min.)
Language,
Grading		 German,
The grading is done with 0 to 15 points according to the examination regulations for the degree program LAaG Mathematics. In the event of failure, a total of 4 attempts are available for the examination.
Origin LAaG Mathematics
Duration,
frequency		 One semester,
Jedes zweite Semester
Person in charge of the module's outline Prof. Dr. Markus Bibinger, Prof. Dr. Hajo Holzmann

Contents

Scientific contents:

  • probability space, events, discrete probability distributions, combinatorics
  • conditional probability, independence, random variables, expected value, conditional expected value, variance, covariance, correlation, moments, general probability spaces and random variables
  • law of large numbers and central limit theorem,
  • descriptive statistics and data types
  • elements of inferential statistics: estimates, confidence sets,
  • hypothesis testing

Didactic contents:

Tasks and short lectures in the exercises on teaching related topics of elementary stochastics as well as projects on selected topics of school mathematics in connection with the current lecture material. Basic terms and topics are given special consideration, e.g.

  • from the intuitive concept of probability to axiomatics
  • historical aspects of probability theory
  • statistical (mis)interpretations of everyday examples

Qualification Goals

Competences:

The students

  • know and use the basic concepts of stochastics and are familiar with statistical thinking,
  • apply the basic principles of mathematical modelling to concrete stochastic questions and in particular take into account the exact demarcation between experiment and mathematical model,
  • compare different concepts and evaluate them with regard to their possible applications in the classroom.

Qualification goals:

The students are familiar with the basic concepts of stochastics, can apply them to concrete tasks and assess their possible applications in class.


Prerequisites

None. The competences taught in the following modules are recommended: Analysis I, Analysis II, Linear Algebra incl. Foundations of Mathematics.


Applicability

The module can be attended at FB12 in study program(s)

  • LAaG Mathematics

When studying LAaG Mathematics, this module must be completed in the study area Advanced Modules.


Recommended Reading

(not specified)



Please note:

This page describes a module according to the latest valid module guide in Winter semester 2019/20. Most rules valid for a module are not covered by the examination regulations and can therefore be updated on a semesterly basis. The following versions are available in the online module guide:

The module guide contains all modules, independent of the current event offer. Please compare the current course catalogue in Marvin.

The information in this online module guide was created automatically. Legally binding is only the information in the examination regulations (Prüfungsordnung). If you notice any discrepancies or errors, we would be grateful for any advice.