Essex Summer School in
Social Science Data Analysis

René Lindstädt

René Lindstädt (PhD Washington University in St. Louis) is Reader in the Department of Government and Director, Essex Summer School in Social Science Data Analysis, University of Essex. Before joining the University of Essex in 2011, he held faculty positions at SUNY Stony Brook and Trinity College Dublin. His main research and teaching areas are political economy, political institutions, formal theory and political methodology. His theoretical interests are in social learning and diffusion, political accountability, strategic communication and cooperation. René's research has been published or is forthcoming in, among others, the Journal of Politics, Comparative Political Studies, European Union Politics, Legislative Studies Quarterly, Journal of Theoretical Politics, Public Choice and NYU Law Review. He is currently working on several projects in the area of (policy) diffusion, with applications to American and comparative politics, and a research project on electoral competitiveness.

1S Introduction to Stata

René Lindstädt, University of Essex
8 - 19 July (two week course / 35 hrs)

Detailed Course Outline [PDF]

Course Content

This course is designed to give students who already have experience in data analysis a basic familiarity with the statistical software package STATA. The course focuses on basic programming skills, covering the manipulation of variables, elementary statistical analyses, data construction, and data management (including working with files at different units of measurement and working with longitudinal data). British Household Panel Survey data are used for illustrative purposes and practical exercises.

Course Objectives

This course exposes participants to the features of STATA. By the end of the course, participants will know how to load data into STATA, how to clean, manage, manipulate, and expand on existing data files, and how to work with multiple files of differing levels of analysis. The course will also highlight the use of some basic statistical procedures and features for manipulating the output from STATA. This course is not designed to teach data analysis or statistics, but to demonstrate applying data analysis techniques using STATA

Course Prerequisites

Participants need an intermediate familiarity with data analysis and an understanding of basic statistical procedures up to and including multiple regression. It is expected that participants understand statistics up to a level that enables them to decide what kind of tests to perform to answer specific research questions. This course does not teach statistics. You should not enrol in this course if you do not understand intermediate level statistics. If you are unsure of your level of knowledge, get in touch with the course instructor before signing up for the course. No prior experience with STATA is required. Participants should be aware that STATA is largely a command-driven program, which is very different from ‘drop-down window’ programmes. Thus, writing programming code and completing exercises from an instructional booklet is a major component of the course.

Reading:

David Pevalin and Karen Robson (2009) Stata Survival Manual, Open University Press.

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