Date: 28 May 2020
Instructor: Tina Hannemann
Fee: £195 (£140 for those from educational, government and charitable institutions).
CMI offers up to five subsidised places at a reduced rate of £60 per course day to research staff and students within Humanities at The University of Manchester. These places are awarded in order of application.
Please note: this is not guaranteed and is considered on a case by case basis. Please contact us for more information.
The course will provide intermediate training in the statistical programming software STATA, which is a popular tool in the field of Social Science. The software is a great tool to deal with a large dataset, for data manipulation and various analysis strategies including extensive and powerful statistical capabilities.
The aim of the course is to familiarise participants with some features of Stata 14 which go beyond the introductory level. Participants will cover the following topics through a combination of lecture and practical sessions:
- Quick review of some more basic operations
- The proper use of weights and weighted tables
- Merging datasets and combining information from different sources for combined analysis
- Strategies of analysis and modelling with the example of logistic regression
On completion of the course, participants will have the necessary familiarity with concepts in Stata to move on to further statistical methods in Stata either in courses and/or continue learning themselves.
Basic operational experiences in STATA are required for the course, as those will not be covered and necessary for the content of this course. However, participants do not have to be advanced users of STATA. Some familiarity with handling datasets (e.g. excel spreadsheets) are also beneficial for the understanding of the course content.
- Diamond, I. and Jefferies, J. (2004) Beginning Statistics: An Introduction for Social Scientists. London, Sage Publications.
- Blaikie, N. (2003) Analyzing Quantitative Data: from description to explanation London, SAGE Publications.