Bridging Courses at the Faculty of Communication and Environment

Bridging courses are intensive courses you can take before starting your studies. They are voluntary and do not carry any credit-point value towards your degree. Bridging courses are designed for students who may not meet the assumed knowledge requirements and want to bridge the gap between school and university studies.

You can join the bridging course without prior registration simply by using the WebEx link provided by the respective lecturer:
Malte Weber: https://hsrw.webex.com/meet/malte.weber1
Sabine Lauderbach: https://hsrw.webex.com/meet/sabine.lauderbach

WebEx can be accessed via your web browser, and it is also possible to join from your mobile phone. You may need to download and install the software, so please allow a few minutes for this. Kindly ensure that you have a working microphone and, if possible, a camera.

If you have any general questions about the bridging courses, please contact Ms Daniela Menzel at: daniela.menzel@hochschule-rhein-waal.de

 

Bridging courses between September 7 - 12, 2026 (Mo - Fr)

Time and Date Topic Language Lecturer
scheduled
Mo-Fr
8.30 am -11.30 am 
online 
Mathematics,
lecture
English M. Weber
scheduled
Mo-Fr
12.30 pm - 3.30 pm 
online 
Mathematik,
Vorlesung
Deutsch M. Weber

 

Bridging courses between September 14 - 18, 2026 (Mo - Fr)

Time and Date Topic Language Lecturer
scheduled
Mo-Fr
8.30 am - 10.30 am 
online 
Mathematik,
Übung
German M. Weber
scheduled
Mo-Fr
10.30 am - 12.30 pm 
online 
Mathematics,
exercise
English M. Weber
scheduled
Mo-Fr
10.30 am - 1.30 pm
online 
Statistik Deutsch S. Lauderbach
scheduled
Mo-Fr
2.30 pm - 5.30 pm
online 
Statistics English S. Lauderbach

 

Course contents

Mathematik (German)

  • Logik und Mengen
  • Elementare Beweisverfahren
  • Zahlensysteme
  • Gleichungen und Ungleichungen
  • Abbildungen/Funktionen
  • Folgen
  • Differenzierbarkeit
  • Vektorräume und Vektoren

Mathematics (English)

  • Logic and Sets
  • Elementary Proof Techniques
  • Number Systems
  • Equations and Inequalities
  • Mappings / Functions
  • Sequences
  • Differentiability
  • Vector Spaces and Vectors

Statistik (German)

  • Teil I: Deskriptives, Lagemaße und Streuung: Mittelwert, Standardabweichung, Ausreißer, Boxplot und Punktdiagramm, Normalverteilung, Schiefe, Kurtosis.
  • Teil II: LaPlace-Wahrscheinlichkeiten, Münzwürfe, P-Wert, Urnenmodelle, Parameterschätzung, Konfidenzintervall, Signifikanzniveau, Alpha und Beta Fehler.
  • Teil III: Statistische Tests, Anpassungsgüte, Optimierungsverfahren, Funktionsweise Chi-Square und Student T-Test (H0/H1 Test).
  • Mini-Aufgabe Chi-Square Goodness of Fit am Beispiel einer Tüte M&M. Case study: Problem des Handlungsreisenden.

Statistics (English)

  • Day 1: Descriptive statistics & relationship between variables (mean, median, quantiles, (co)variance, correlation)
  • Day 2: Probability & set theory (random variables, Laplace, urn problem, conditional probability, Bayes' theorem)
  • Day 3: Distributions & graphical representations (discrete/continuous distributions, probability density function, cumulative density function)
  • Day 4: Estimations & hyptheses (point & interval estimations, confidence-intervals)
  • Day 5: Statistical tests & outlook (t-, chi-square-tests)