Quantitative Research Skills
Coordinator: prof.dr. Peter van Bodegom, Dr. ir. Marco Visser
To participate in Quantitative Research skills, students need to have completed at least 48 EC of the first year MSc courses.
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 on Brightspace. We expect all (prospective) students to have watched and acted upon the video prior to the course. It is also 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 analyses 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 upon these concepts, applied exercises will be introduced with increasing complexity starting from a recap on regression towards 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.
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
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.
Weekly on Mondays from 9.15 to 11.00 h.
Assessment is based on the grades of three dedicated assignments. Each assignment weighs 1/3 of the final grade and are done individually or in groups of maximum 2 to 3 persons (depending on the assignment). 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 firstname.lastname@example.org