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Quantitative Research Skills


Title course:

Quantitative Research Skills

Coordinator: prof.dr. Peter van Bodegom, Andreea Nanu MSc

Admission requirements

Not applicable. For this course, we assume a basic knowledge and understanding of statistical methods and theory. Such knowledge and understanding is assumed to be captured by the general prerequisite of the MSc Governance of Sustainability programme of 8EC and quantitative skills. An elaboration of the requirements regarding prior (statistical) knowledge is provided in an on-line video that is shared with all (prospective) students attending the course.
It is assumed that all students have (R and) Rstudio installed on their private devices prior to the course.


A core component of the scientific cycle is the design, execution and evaluation of data analysis. In most natural sciences, such data analysis encompasses a quantitative or statistical analysis. Together with qualitative research skills, quantitative research skills are thus at the core of research evaluations for future ‘change maker’ acting at the interface of governance and natural sciences (in relation to sustainability). A comprehensive understanding of quantitative research skills is thus essential for performing research at this interface, e.g. in the MSc thesis or as a graduate. Moreover, many actions for sustainability and its governance are supported by statistical claims. Being able to evaluate those claims is therefore an essential skill for a change maker. The latter demands not only a comprehensive understanding of the key concepts and assumptions, but also experience in performing such analysis in order to be able to critically evaluate the merits of the analysis chosen.
Based on this vision, this course starts with a recap of key concepts in statistics and the core assumptions to evaluate its use and misuse. Building up on these concepts, applied exercises will be introduced with increasing complexity starting from a recap on regression towards 2-way ANOVAs, ANCOVAs, multiple regression and multivariate analysis. Special attention is paid to meta-analysis, as this method – in addition to the statistical methods identified above – is often used to support governance claims. The entire theory is embedded in practice by using examples from scientific literature and governance-related reports and using real-life examples and data in the assignments.

Learning goals

  • Understand the fundamental statistical concepts, including its assumptions, needed for the execution of statistical analysis and for evaluating statistical claims

  • Choose the best suitable statistical design for a given research question and experimental design

  • Run and interpret statistical analysis for a selected suite of statistical methods

  • Critically read, verify and judge statistical claims in literature

Education format

Weekly (on-line) interactive sessions are provided. Within each of the sessions, questions and comments on pre-recorded videos will be dealt with. These videos target one or a few statistical concepts. These Q&A sessions may be done in a plenary fashion or in break-out rooms. We also ask active participation of the students to bring in their own examples suitable to the topic discussed that week. Moreover, the homework from the previous week will be discussed as well as new homework will be introduced.
Homework consists of hands-on assignments, either to analyse claims from (short) scientific papers and/or to execute your own analysis and provide the appropriate interpretation, plus watching and digesting the information from videos. All analyses are done in Rstudio for which essential codes for the assignments are provided in the assignment texts.

Class Schedule

Weekly on Mondays from 9.15 to 11.00 h.

Assessment method

Assessment is based on the grades of three dedicated assignments. The first two assignments, weighing 25% of the final grade each, are done individually or in groups of maximum 2 to 3 persons. The final assignment (50% of the final grade) is done individually and is time-constrained. Assignments consist of an analysis of claims from literature and/or executions of statistical analysis and its interpretation.


BrightSpace University Leiden will be used for communications and distributing study material.


MSc Governance of Sustainability students can register for the course and exam via uSis. Other students need to contact the study advisors of the programme via

Contact information