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

CS 461 — Internship Statistics
(dt. Praktikum zur Statistik)

Level, degree of commitment Practical module, depends on importing study program
Forms of teaching and learning,
workload		 Internship (2 SWS),
90 hours (30 h attendance, 60 h private study)
Credit points,
formal requirements		 3 CP
Course requirement(s): None, but attendance is compulsory.
Examination type: The examination consists of an oral presentation with a written assignment.
Language,
Grading		 German,
The module is ungraded in accordance with the examination regulations for the degree program B.Sc. Computer Science.
Subject, Origin Computer Science, B.Sc. Computer Science
Duration,
frequency		 One semester,
In the summer semester / as a block course during the lecture-free period in spring
Person in charge of the module's outline Prof. Dr. Dominik Heider

Contents

The practical course is based on the statistics software ''R''. First, the functionalities of ''R'' are introduced. Subsequently, the theory is briefly introduced to the topics listed below. The methods introduced are investigated with ''R'' on the basis of simulations and applied to data sets.

Topics (only a selection is covered)

  • Basics in dealing with R
  • Random variables and their simulation
  • descriptive statistics and graphics
  • Point and interval estimation
  • Statistical hypothesis tests
  • Analysis of multivariate data
  • Linear Regression
  • Covariance and variance analysis
  • Generalized linear models

Qualification Goals

The students shall

  • learn how to use the statistics software R,
  • be able to investigate statistical methods by means of suitable simulations,
  • be able to apply appropriate statistical methods to given data sets and problems,
  • to process the results obtained in an appropriate manner in writing,
  • gain experience in teamwork and work organisation during the development of tasks.

Prerequisites

None. The competences taught in the following modules are recommended: Basic Linear Algebra, Basic Real Analysis, Introduction to Statistics.


Recommended Reading

  • Will be announced in the course



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.