KGLM 2015 - Introduction to Statistical Reasoning and Quantitative Methods

This course is about the core notions of quantitative research for the social sciences, based on three fundamental blocks of knowledge: essential statistical concepts, cross-sectional data, and various forms of regression analysis. By design, this course will approach quantitative analysis through methods and examples taken from various branches of the social sciences, with some specific applications to public health, political science and sociology. We will focus on research design, as to make sure that we ask valid questions, based on sound hypotheses as well as reliable data, and draw correct inferences. Throughout the course, we will introduce and explain some essential statistical operations that can be used to that end. Last, we will introduce statistical software and work through the procedures to produce statistical tests and visualizations of quantitative data. The emphasis of the course is set on conceptual understanding and statistical reasoning, and each session will apply statistical procedures to real data. Handbook chapters will be used to cover the statistical side of the course, while class sessions will focus on practical experience.

Antoine JARDIN

English

This course requires at least two hours of weekly homework. Students with little or no computer skills should expect to work at least one additional hour, students with little or no background in the social sciences should expect to work at least one additional hour. All skills learnt in this course are immediately transferable to other courses.

No previous knowledge in any of the course topics is required for taking the course, but some computer and Internet skills as well as a genuine interest in understanding why and how we use quantitative information to understand society will prove useful.

Autumn 2021-2022

Students are all required to work in pairs on personal research projects, on which they will hand in two intermediate drafts and one final paper written along current scientific standards.

12 sessions of 2 hours.The course is almost entirely computer-based and uses statistical software as well as online resources. Students will be strongly encouraged to bring their own laptops to class. Full attendance and active participation in class are required from all students, as course sessions are non-redundant and as questions answered in class will not be answered by email. If time permits, a few optional pre-class workshops will be set up before some of the course sessions.