The Centre for Census and Survey Research (www.ccsr.ac.uk) at the University of Manchester will be running three one-day training course in statistical analysis in June. A small number of places are still available. See www.ccsr.ac.uk/courses/list
Causal Modelling in Stata – 6th June 2011
Course Requirements: Requires some previous experience with doing regression or statistical tests.
Course Summary: Many analysts move from simple regression to more complex causal modelling as their professional life develops. This course introduces basic techniques that are helpful for making statistical inferences in the intermediate level models: using a ‘long’ format panel data set; applying regression to panel data; drawing out causal interpretations. The course will also cover some causal concepts, describe statistical approaches to causal inference, give worked examples of regression models, and give hands-on experience in applied causal analysis using STATA.
Fuzzy Set Analysis – 7th June 2011
Course Summary: This short course focuses on how to create fuzzy sets, and analyse them causally. The result is a simplified summary of the multiple causal pathways present in the data. Fuzzy sets can deliver three sets of results:
1) data reduction, where from 3 to 6 variables are reduced to one;
2) causal analysis, both within the set of cases and aiming at inference to a population; and
3) a separation of necessary cause from sufficient cause, taking into account mixtures of causes rather than having a linear separation of each cause.
Fuzzy sets are a way of introducing orderings into any table of data. Each case is ranked (or calibrated) on its membership in sets (e.g. the set of chronically poor households.) We then study causality using fsQCA software or STATA “fuzzy” command. Tests of sufficient causality and of necessary causality are conducted separately.
Introduction to R – 20th June 2011
Course Summary: This course is aimed at people who wish to familiarise themselves with the freely available statistical analysis software R. R is a command language that can be used to carry out standard statistical analyses but also has powerful facilities to enable users to create their own routines or implement methods designed by other researchers. The course will: introduce participants to the R environment; explain how to enter data and run simple descriptive statistical methods; describe how to run standard procedures; show how to run commands designed by other researchers and how to develop commands for non-standard analyses. For background materials, software and reading please go to http://www.r-project.org/
For more information and to book please go to www.ccsr.ac.uk/courses/list