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This entry is from Winter semester 2018/19 and might be obsolete. You can find a current equivalent here.

CS 360 — Introduction to Statistics
(dt. Grundlagen der Statistik)

Level, degree of commitment Advanced module, depends on importing study program
Forms of teaching and learning,
workload		 Lecture (2 SWS), recitation class (2 SWS),
180 hours (60 h attendance, 120 h private study)
Credit points,
formal requirements		 6 CP
Course requirement(s): Oral or written examination
Examination type: Successful completion of at least 50 percent of the points from the weekly exercises as well as at least 2 presentations of the tasks.
Language,
Grading		 German,
The grading is done with 0 to 15 points according to the examination regulations for the degree program B.Sc. Computer Science.
Subject, Origin Computer Science, B.Sc. Computer Science
Duration,
frequency		 ,
each winter semester
Person in charge of the module's outline Prof. Dr. Dominik Heider

Contents

  • Statistical key figures
  • Probability theory, probability measures and spaces
  • Random variables and their distributions
  • Important probability distributions, statistical tests

Qualification Goals

The students shall

  • Acquire basic knowledge and skills in statistics, in particular with regard to statistical indicators, distributions, distribution densities, hypotheses and hypothesis tests,
  • Recognize cross-connections to computer science,
  • practice mathematical and in particular statistical ways of thinking and working on concrete questions, also on technically motivated problems,
  • develop mathematical and statistical intuition and learn how to translate it into precise terms and formal justifications,
  • to train your abstraction skills,
  • acquire all the necessary prerequisites for successful participation in the statistics internship,
  • improve their oral communication skills in the exercises by practicing free speech in front of an audience and during discussion.

Prerequisites

Translation is missing. Here is the German original:

Keine. Empfohlen werden Grundkenntnisse in Grundlagen der Analysis und Grundlagen in der linearen Algebra.


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 2018/19. 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.