t.BA.XXM6.AS1.19HS (Algebra and Statistics 1) 
Module: Algebra and Statistics 1
This information was generated on: 22 February 2024
Algebra and Statistics 1
Organised by


Version: 4.0 start 01 August 2022

Short description

This module covers the topics of linear equations, matrix algebra and vector geometry as well as elementary probability theory and discrete random variables.

Module coordinator

Ines Stassen Böhlen (sses)

Learning objectives (competencies)

Objectives Competences Taxonomy levels
You become acquainted with the mathematical tools and concepts required for the engineering modules. You familiarize yourself with the mathematical way of thinking and practice your ability to abstract.    
You are able to
- determine the solution set of a system of linear equations.
- determine the number of solutions of a given system of linear equations using suitable criteria.
F,M K2, K3
You are able to
- calculate the sum, product, transpose, inverse and determinant of given matrices.
- determine whether a square matrix is invertible, i.e. whether its columns are linearly independent using suitable criteria.
F,M K2, K3
You are able to
- calculate the sum, a certain linear combination, the dot and cross products of given vectors.
- describe lines, planes, circles and spheres using equations.
- determine intersections of lines, planes, circles and spheres.
- determine whether two given vectors are orthogonal or collinear using suitable criteria.
F,M K2, K3
You are able to
- define probability distributions for discrete event spaces and calculate probabilities of events.
- build basic stochastic models, define random variables, derive their probability density functions (PDFs) and their cumulative distribution functions (CDFs) and calculate probabilities.
- explain the meaning of measures of center and variability for random variables.
- calculate the expected value, the variance and the standard deviation of discrete random variables.
- calculate conditional probabilities.
- build event tree diagrams.
- formulate and apply Bayes' theorem, the theorem of total probability and the multiplication theorem for event tree diagrams.
F,M K2, K3
You are able to use the competencies listed above to solve more complex problems.
F,M K3

Module contents

Systems of linear equations
Matrix algebra

Vector geometry
Elementary probability theory
Discrete random variables

Teaching materials

Depending on the lecturer.

Supplementary literature

Gramlich, Günter M. (2014): Lineare Algebra. Eine Einführung. 4. Aufl. München: Carl Hanser Verlag.
Sachs, Michael (2018): Wahrscheinlichkeitsrechnung und Statistik: für Ingenieurstudenten an Fachhochschulen. 5. Aufl. München: Carl Hanser Verlag.
Papula, Lothar (2017): Mathematische Formelsammlung. Für Ingenieure und Naturwissenschaftler. 12. Aufl. Wiesbaden: Springer Vieweg.


Mathematics of the technical vocational baccalaureate.

Teaching language

(X) German ( ) English

Part of International Profile

( ) Yes (X) No

Module structure

Type 2b
  For more details please click on this link: T_CL_Modulauspraegungen_SM2025


Description Type Form Scope Grade Weighting
Graded assignments during teaching semester 1 test written 45 min Grade 20%
  regular assessment (e.g. online tests) written   Grade 10%
End-of-semester exam exam written 90 min Grade 70%



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: Algebra und Statistik 1 - Vorlesung
Algebra und Statistik 1 - Vorlesung


  • No module description is available in the system for the cut-off date of 01 August 2099.