ERIM Summer School


Six advanced courses

Would you like to improve your data analysis skills or your competences in a specific field? Then start the summer with one or more short, specialised courses at ERIM Summer School. In a group of at most 30 participants, you will be taught by academics who are experts on the subject matter.

Fully taught in English, our courses are open to graduate students (i.e. research master and PhD level), researchers and professionals from the Netherlands and beyond. Upon completing a course, you will receive a certificate indicating the number of European credits (ECTS) earned.

Within the ERIM Summer School 2017, you can choose from the following courses:


Testing and Interpreting Moderation and Mediation with SPSS

19 & 20 June 2017
by Professor Jeremy Dawson

Mediation and moderation are crucial ways of expanding and testing theory. Moderators are variables that affect the strength and/or direction of relationships between other variables, while mediators are intermediary mechanisms that explain the relationships between other variables. This course will cover how moderation and mediation can be tested, both separately and together, using SPSS.


My First Bayes: A Gentle Introduction to Bayesian Analysis

21 to 23 June 2017
by Dr Rens van de Schoot

Since the beginning of the 21st century, Bayesian statistical methods are slowly creeping into all fields of science and are becoming ever more popular in applied research. This increase is specifically due to recent computational advancements and the availability of Bayesian estimation methods in popular software and programming languages. Moreover, the use of Bayesian methods has increased because this estimation framework can handle some commonly encountered problems in orthodox statistics.


Introduction to Data Visualization, Web Scraping, and Text Analysis in R

3 and 7 July 2017
by Dr Jason Roos

Many researchers rely on data that are obtained from a wide variety of online sources, including web sites, social media, and external data providers. This course introduces you to procedures for collecting, preparing, analysing, and visualising such data. You will learn about core ideas in data visualization, web scraping, and text analysis while gaining practice writing, debugging, and tracking changes to code in R.

Executive Compensation and other Managerial Incentives

21 to 23 June 2017
by Professor David Yermack

This course surveys leading academic research in executive compensation and related areas of managerial incentives, such as stock ownership, insider trading, the threat of replacement, and the private benefits of control. The material will be presented in an interdisciplinary framework, integrating issues arising in economics, finance, accounting, and law. Lectures will focus on published academic papers but will also highlight the importance of the course topics in real-world business settings.


Necessary Condition Analysis: theory and practice

26 & 27 June 2017
By Professor Jan Dul

Necessary (but not sufficient) conditions are widespread in real life and therefore relevant to various research areas, such as management, business research, sociology, and psychology. But until recently no technique was available to identify necessary conditions in datasets. Traditional (regression based) data analysis techniques fail to do so, even though they are frequently applied for exactly that matter. Necessary Condition Analysis (NCA) is a new technique that can do the job (Dul 2016). 


Charting New Territory for Qualitative Methods: Practicing new modes of Fieldwork, Headwork and Textwork to capture new realities of work

4 to 6 July 2017
by Dr Michael Smets

Research methods must first and foremost be able to accurately capture and represent the world we study. How have qualitative research methods kept up with the new realities of work and the theoretical phenomena we are interested in? This course charts the territory of novel qualitative methods for data collection, analysis and presentation, or  - as Van Maanen (2011) calls them: “fieldwork”, “headwork” and “textwork”. We will devote one day to each of these research phases.