Online Course Guide of WHU –

Find all modules and courses of our degree programs.

Please use the filters below to select the term (spring or fall) as well as the respective program (BSc, MSc, MBA, Exchange, Doctoral) of your choice for an overview of all modules offered at WHU. The courses are listed under the modules. Please click on a module to see which courses are part of it. If you would like to find out more about a certain course, click on the name of the course to see detail information. The location of the lecture will be revealed after your course registration on myWHUstudies.

Spring term counts from January - August, fall term counts from September - December.

Important for Exchange Students: As the Full-Time and Part-Time MBA Programs utilize a modular course structure, the dates on which students begin and end the exchange are flexible. Please find here a chronological overview of the preliminary course offering for Fall and Spring.

Spring 2021  ›  Bachelor of Science  ›  Bachelor of Science - 4th Semester  ›  Quantitative Research Methods

Quantitative Research Methods

Course Code:
Prof. Dr. Michael Massmann
Course Type:
BSc Course
Week Hours:
Spring 2021
(Please note that exchange students obtain a higher number of credits in the BSc-program at WHU than listed here. For further information please contact directly the International Relations Office.)
The purpose of this course is to introduce modern econometric techniques and apply them to real world data sets. The material covered in this course includes an in-depth analysis of the linear regression model, least-squares estimation and statistical inference in this setting. Subsequently, nonlinear regression models are discussed and an introduction to panel data as well as stationary time series analysis is given. Empirical data sets are taken from finance and macroeconomics.
11:30 AM till 03:15 PM
Friday, 19/02/2021
03:30 PM till 06:45 PM
Monday, 22/02/2021
11:30 AM till 03:15 PM
Tuesday, 13/04/2021
11:30 AM till 03:15 PM
Thursday, 29/04/2021
02:00 PM till 05:00 PM
By the end of this course, students will have a sound understanding of fundamental
econometric techniques and will be able to apply them to real world data sets using
modern software.
Stock and Watson (2015): Introductory Econometrics
The course takes the form of interactive lectures with exercises: on the one hand, theoretical material is presented and illustrated by means of empirical examples using the R statistical computing environment; on the other hand, participants are given exercises to practice the use of newly-learned concepts, both conceptually and on the computer.
written exam
Familiarity with the topics covered in Statistics I and II is assumed.