Probability und Statistics

11B2075

Bachelor

German

5.0

irregular

1 semester

Basic concepts of probability theory are taught, which on the one hand are used in many areas 
areas and are also a prerequisite for understanding statistical methods. 
methods. Building on this first part, common statistical methods and linear models are also covered. 
linear models. Both are important tools for analysing data and enable conclusions to be drawn from data. 
drawing conclusions from data.

1. basics of probability theory:
Concepts of events and probability, conditional probability, total probability, independence, random variables, laws of large numbers 
probability, independence, random variables, laws of large numbers, 
standard distributions. 
2. introduction to the basic methods of descriptive and inferential statistics: 
Common estimation and testing procedures 
3. linear models: 
Analysis of variance and covariance, stochastic treatment of linear regression.  
Supplementary: presentation of a statistics package (e.g. R)

The total workload for the module is 150 hours (see also "ECTS credit points and grading").

• Project Report, written or
• Written examination

Examination: see applicable study regulations

Project report (written): 5–10 pages, accompanying explanation: approx. 15 minutes

Prerequisites for successful participation are knowledge of mathematics in the field of real functions as well as differential and integral calculus, as taught in the Mathematics 1 and 2 modules of the Electrical Engineering or Computer Science degree programmes. 

Students know and have a good understanding of the basic concepts, facts and conclusions of probability theory and statistics.

Students can model events of medium complexity and calculate the associated probabilities. 
calculate probabilities. 
They can handle common statistical methods and evaluate their results. They can 
in particular assess which statistical method is appropriate for a given problem. 

• Gervens, Theodor

• Gervens, Theodor