École urbaine, Master in Governing the Large Metropolis
a theorical part, to introduce Geographic Information concepts and GIS features ; a practical part, to learn how to handle, process and analyze Geographic Information with the software QGIS. Required reading : [book] Longley P. A., Goodchild M. F., Maguire D. J. & Rhind D. W. (2015). Geographic Information Science and Systems, 4th Edition. Wiley ; [book] Burrough P. A., McDonnell R. A. & Lloyd C. D. (2015). Principles of Geographical Information Systems, 3rd Edition. Oxford University Press ; [article] Goodchild M. F. (1992). Geographical Information Science. International Journal of GIS, vol. 6, n°1 ; [article] Goodchild M. F.(2010). Twenty years of progress : GIScience in 2010. Journal of Spatial Information Science, n°1.
Pedagogical method : 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. Course Description : This course is about the core notions of quantitative research for the social sciences, based on three fundamental blocks of knowledge : essential statistical concepts, crosssectional 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. Required reading : Briatte, F. 2013. This is Stata. ; Feinstein, C.H. and Thomas, M. 2002. Making History Count..
INTRODUCTION TO STATISTICAL REASONING AND QUANTITATIVE METHODS
Semester : Autumn Number of hours : 24 Language of tuition : English
Teachers : François BRIATTE (PhD Candidate University of Grenoble), Haley MCAVAY (PhD candidate, Sciences Po). Prerequisite : 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. Pedagogical format : Workshop Course validation : 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. Workload : 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.
INTRODUCTION TO STRUCTURAL ANALYSIS AND SOCIAL NETWORKS
Semester : Autumn Number of hours : 12 Language of tuition : English
Teachers : Jaime MONTES LIHN (Researcher). Prerequisite : None Pedagogical format : Workshop 2223