Design and Analysis of Experiments (Design und Analyse von Experimenten)



Semester: Winter Semester 2023/24
Study programs: Business Administration Master, Business Informatics Master
Scope: 2 SWS/3 CPs
Exam: Term Paper/Presentation
Date/Time: Presence Event, 24.01.2024 (C3.1, 1.02) & 25.01.2024 (C3.1, 1.02) & 26.01.2024 (C3.1, 3.01), see LSF
Contact: elena.banowitz(at)
Registration: Please register by e-mail to elena.banowitz(at) by the end of December 2023.
Limited number of participants: 20




This course is intended for master's and doctoral students who plan to conduct experimental and quasi-experimental research in business administration (e.g., marketing or organizational behavior) and related disciplines (e.g., psychology).


Experimental research is a common method within business administration used specifically to study consumer behavior. Experimental research is a collection of techniques in which various types of manipulation are used to test causal relationships. Typically, one or more independent variables are manipulated to determine their effects on the dependent variables. 

This course provides an overview of the fundamentals of experimental research. This includes defining a research problem, transforming the problem into a hypothesis, and then developing an appropriate experimental design and sample.

To successfully pass the course, students must write a term paper. Within the term paper, the primary task is to develop an experimental design based on either a self-selected topic or an assigned research question. Besides the data collection, all steps should be presented and discussed within a short research article (written paper). The structure of the article could be as follows:

  1. Introduction to the problem - Why look into it further?
  2. Brief description of previous studies in this area
  3. Methodology
  4. Data Analysis
  5. Anticipated Results



Lecture Notes WS23/24




Learning Goals


The primary goal of the course is to familiarize students with various concepts and tools to collect and analyze experimental data. The secondary goal is to provide students with the foundations for methodologically evaluating other work done by behavioral scientists. 

In the course, experimental design and analysis will be approached from the perspective of a behavioral scientist rather than a statistician. Thus, the emphasis is on the judicious use of data collection methods and analysis techniques for an accurate (in the sense of publishable) theory test. However, although statistical concepts are covered extensively (to ensure that procedures and techniques are applied judiciously), statistical theory per se is not the focus.

In addition to the above objectives, the course provides students with the opportunity to analyze pre-designed data sets and to explore SPSS. This is a widely used statistical program for processing and analyzing data. By the end of the course, students should be familiar with the basic functions of SPSS.


  • Field, A.P. & Hole, G. (2003): How to design and report experiments. London: Sage.
  • Shadish, W.R., Cook, T.D. & Campbell, D.T. (2003): Experimental and Quasi-Experimental Design for Generalized Causal Inference, Houghton-Mifflin.
  • Maxwell, S.E. & Delaney, H.D. (2004): Designing Experiments and Analyzing Data: A Model Comparison Perspective (2nd ed). Lawrence Erlbaum: Mahwah, NJ.
  • Williams, L.J., Krishnan, A. & Abdi, H. (2009): Experimental Design and Analysis for Psychology, Oxford University Press.
  • Seltman, H.D. (2012): Experimental Design and Analysis,