The Nuffield/FLAME University Experimental Summer School will be held in Pune, India in conjunction with the FLAME University. At the moment we schedule one session this year which takes place from 16-27 January, 2017.
The course covers the design, implementation, and analytic tools necessary for conducting social science experiments. In the ﬁrst week, the focus will be on laboratory experiments. After an introduction in experimental designs and a review of recent topics in experimental social sciences, the reminder of the ﬁrst week will be hands-on lab experiments. Participants will learn how to program experiments with z-Tree, work with the subject recruitment software, analyse experimental data and be able to run a lab experiment at the Nuffield Centre for Experimental Social Sciences. In the ﬁrst half of the second week, the course will cover ﬁeld and online experiments. Moreover, in two afternoon sessions, participants will have the opportunity to present their own experimental research and receive feedback from an experienced team of instructors. The remainder of the second week will cover topics of causal inference and experimental approaches to data analysis. Upon completion of the course participants should be able to (1) formulate Research questions that can be addressed using experiments, (2) design and carry out experiments, and (3) analyse and interpret results from social sciences experiments.
The course is appropriate for participants from any discipline who expect to include experimental social research as part of their research agenda. It is also appropriate for participants who want to become informed consumers of experimental research scholarship.
Participants should have a basic background in research design and statistics. For example, with respect to research design, they should understand basic concepts such as exogeneity, control group, and confounding effects. With respect to basic statistics, they should understand the principals of ordinary least squares regression; how to calculate simple measures of association; and have some familiarity with a statistical software package. The hands-on experimental data analysis lab sessions will use R. Participants not familiar with R are strongly advised to attend the Introduction in R, held throughout the first week