Attendance dates:February 2020: 24, 25, 26
Time commitment: 3 days
Stag Hill campus, University of Surrey, Guildford, Surrey GU2 7XH
This module investigates the underlying principles and uses of statistical models and not on the mathematical and statistical theory. It will give you a solid empirical grounding to be able to critically evaluate the findings from a wide range of quantitative social science research
You will get hands-on experience of estimating a number of different statistical models in R, engaging with important issues including how to select an appropriate model, assessing the adequacy of a fitted model (in comparison to alternative models), and the statistical and substantive interpretation of the results.
On successful completion of this module, you will be able to:
- Have a critical awareness of the rationale and terminology of statistical modelling (C)
- Be able to engage with existing quantitative research, highlighting its key strengths and weaknesses (C and K)
- Have a comprehensive understanding of the logic of model development and testing (C and K)
- Be able to develop multiple regression, logistic regression, multinomial logistic and poisson regression models and critically evaluate the results (P and T)
- Be able to clearly tabulate and present the results of regression outputs (P and T)
This module elaborates on quantitative approaches to social science, combining this with practical model building experience and critique using R.
Indicative content includes:
- Designing and building statistical models to answer social science questions
- The general linear model
- Operationalising concepts and selecting variables
- Interpreting results and finding the narrative.
Practical workshops will provide you with experience of:
- Linear regression
- Logistic regression
- Multinomial regression
- Poisson regression
- Interaction effects and nonlinear relationships
- Model fit and diagnostics
- Missing data adjustments.
Learning and teaching methods
- Practical workshops in R
- Group discussion and feedback
Ian is a quantitative social scientist with particular expertise in multilevel modelling, survey methodology and missing data.
View our recommended reading list.
There are no formal entry requirements for this module.
You should have some knowledge of regression.
Fees and funding
Price per person:
£595Government and commercial sector applicants
£495Education and charitable sector applicants
Terms and conditions
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