Statistical Tools for Social Scientists
A 2nd Course in Applied Statistics
Eugène Horber is professor emeritus of methodology at the Department of political science and International relations, University of Geneva.
He holds a PhD degree in
Political Science and has taught social
science methodology (both quantitative and qualitative), applied computer science, and
statistics at the University of Geneva.
He is the director of the
Swiss Summer School (Social Science Methodology); main teaching activities
in the past include the Essex Summer School, the Carcassonne Summer School,
the PRESTA Progamme (EU programme for South America), Eurostat/TES, ENSAE (Paris) and ENSAI (Rennes).
His research interests and publications are in the area of statistical
methodology (data exploration, visual data analysis),
survey research and aggregate data analysis, as well as applied computer science (didactical software, hypertext) and computer assisted qualitative data analysis.
He is the author of a software package for exploratory data analysis.
Statistical tools and statistical thinking are an essential part of the methodology of many scientific disciplines, including the empirical social sciences. This intermediate statistics workshop presents tools dealing with many variables (multivariate analysis): building models with several variables and reducing complexity (data reduction). The focus is methodological, conceptual and practical, oriented towards the application of these tools to typical analysis problems in social research.
At the end of the workshop, active participants should be able to
- Understand and critically assess publications in their scientific field using statistical techniques
- Apply the various statistical tools to their own research projects, within a well designed and defined, theoretically grounded, as well as realistic (i.e. applicable) framework.
The aim of the workshop is to provide
- Knowledge and practical skills with data and statistical software, as well as awareness of both the potential and the shortcomings and limitations (assumptions, pitfalls) of commonly used statistical tools.
- Sound foundations of knowledge and skills
with statistical tools applied to the Social Sciences for participants who had an introductory course in statistics and need to go beyond basics.
The various tools will be presented and discussed using numerous examples. Participants will then apply these tools in the context of their projects (hands-on learning). (Software used: IBM SPSS Statistics)
After a quick review of basic statistics, the following topics will be presented:
- Building models using regression techniques:
- Multiple linear regression; regression assumptions and diagnosis; analysis of residuals
- Linear Regression with categorical variables
- Logistic regression
- Other regression types (overview)
- Data Reduction techniques
- Unidimensional scaling: Likkert, Guttman, ...
- Multidimensional scaling: Principal component analyis, factor analysis
- Dunteman, George Henry (1989). Principal Components Analysis. Sage.
- Kim,Jae-On & Mueller, Charles W.(2015) Introduction to Factor Analysis: What It Is and How to Do It. Sage.
- Lewis-Beck, Colin & Lewis-Beck, Michael S. (2015). Applied Regression: An Introduction. Sage
- McIver, John, and Edward Carmines(1981). Unidimensional Scaling. Sage.
- Schroeder,Larry D., Sjoquist, David L., Stephan, Paula E. (2017). Understanding Regression Analysis: An Introductory Guide. Sage.
- Tabachnick, Barbara G. & Linda S. Fidell (2006). Using Multivariate Statistics. 6th ed. Pearson.
- You should be familiar with the following tools and concepts, covered by any introductory class or textbook:
Descriptive statistics: Numerical and graphical summaries;
basics of linear regression; analysis of tables of means and crosstabulations; basics of statistical inference and hypothesis testing.
(Introductory statistics: References and advice
- Basic skills with statistical software.
If you wish to refresh your basic statistics and skills with SPSS, consider to register for the free 2-day
Statistics/SPSS refresherpreliminary workshop as well.