Camille Fournier De Lauriere: Catalogue data in Autumn Semester 2024

NameMr Camille Fournier De Lauriere
Address
Internat. Beziehungen, Bernauer
ETH Zürich, IFW C 41.1
Haldeneggsteig 4
8092 Zürich
SWITZERLAND
Telephone+41 44 632 02 64
E-mailcamille.fournierdelauriere@ir.gess.ethz.ch
DepartmentHumanities, Social and Political Sciences
RelationshipLecturer

NumberTitleECTSHoursLecturers
860-0041-00LData Analysis for Public Policy Research Restricted registration - show details 4 credits2VE. K. Smith, C. Fournier De Lauriere
AbstractThis course covers the necessary fundamentals for the use of statistics to understand policy. Theoretically the course will provide a survey of foundational concepts and techniques statistics and mathematics. The applied part of the course will focus on implementing these techniques in R, as well as the practical skills required to develop their own data based research projects.
Learning objectiveGain a familiarity with foundational concepts and techniques in statistics, and be able to apply these to new problems. Be comfortable independently conducting a variety of tasks in R, such as data cleaning, visualisation and analysis. Produce summaries of statistical analyses that non-specialists can understand.
ContentThis course introduces students to the necessary fundamentals of statistics, and its application, to understand policy. Theoretically the course will provide a survey of foundational concepts and techniques statistics and mathematics. The applied part of the course will focus on implementing these techniques in R, as well as developing the practical skills in the language required to be able to independently conduct data based research projects.

By doing so, students will gain a familiarity with foundational concepts and techniques in statistics, and be able to apply these to new problems. Students will also develop the requisite skills to be able to independently conduct a variety of tasks in R, such as data cleaning, visualisation and analysis. Finally, students will be able to produce summaries of statistical analyses that non-specialists can understand.