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HSRW – Hans Jürgen Landes

Bridging Courses

Bridging courses are intensive courses designed to help you prepare for your degree before your studies begin. Participation is voluntary and no credit points are awarded. You can use the courses to refresh your existing knowledge and fill in any small gaps before starting your studies.

Here you’ll find the courses currently planned for 7 to 18 September 2026. Please note that the programme may still be subject to change at short notice.

Registration

No need to register in advance – just use your lecturer’s Webex link to join the preparatory course:

Malte Weber
hsrw.webex.com/meet/malte.weber1

Sabine Lauderbach
hsrw.webex.com/meet/sabine.lauderbach

You can join Webex directly in your browser or on your smartphone. Depending on your device, you may need to download and install the Webex app first, so allow a few extra minutes for this. Make sure your microphone is working and, if possible, have a camera ready too.

Courses

Bridging courses from 7 to 12 September 2026 (Mon–Fri)

Time

Expected to be online
Mon – Fri
8.30 am – 11.30 am
 

Course

Mathematics,
lecture

Language

English

Lecturer

Malte Weber

Expected to be online
Mon – Fri
12.30 pm – 3.30 pm
 

Mathematik,
Vorlesung

German

Malte Weber

Bridging courses from 14 to 18 September 2026 (Mon–Fri)

Time

Expected to be online 
Mon – Fri
8.30 am – 10.30 am
 

Course

Mathematik,
Übung

Language

German

Lecturer

Malte Weber

Expected to be online 
Mon – Fri
10.30 am – 12.30 pm
 

Mathematics,
Exercise

English

Malte Weber

Expectedto be online 
Mon – Fri
10.30 am – 1.30 pm
 

Statistik

German

Sabine Lauderbach

Expected to be online 
Mon – Fri
2.30 pm – 5.30 pm
 

Statistics

English

Sabine Lauderbach

Course content

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)
     

Contact

Platzhalter
Daniela Menzel
Dean's Office / Secretary to the President
+49 2842 90825 9662

Kamp-Lintfort Campus

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