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 Academic Year: | 2017/8 |
| Owning Department/School: | Faculty of Humanities & Social Sciences (units for MRes programmes) |
| Credits: | 6 [equivalent to 12 CATS credits] |
| Notional Study Hours: | 120 |
| Level: | Masters UG & PG (FHEQ level 7) |
| Period: |
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| Assessment Summary: | CW 50%, EX 50% |
| Assessment Detail: |
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| Supplementary Assessment: |
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| Requisites: | |
| Description:
| Aims: This is an advanced level quantitative methods course designed to equip students with a range of technical skills covering the major experimental and quasi-experimental approaches to data analysis used in the social sciences. The primary aims of the unit are to: * Introduce a number of approaches to data analysis used in different disciplinary backgrounds across the social sciences. * Provide students with both the theoretical understanding of these techniques and practical experience in utilizing them. * Facilitate critical appraisal of research findings using these techniques. * Provide students with an insight into how these various quantitative methods could be applied in their own field of interest. Learning Outcomes: Students will: * acquire knowledge of and proficiency in the use of advanced quantitative techniques drawn from a range of social science disciplines; * be able to produce, use and interpret the results from a variety of regression models (standard multi-variate, limited dependent variable, instrumental variables) * be able to produce, use and interpret the results from quantile regression models (unconditional and conditional); * be able to produce, use and interpret the results from difference in difference methods; * be able to produce, use and interpret the results from various techniques applied to longitudinal data (fixed and random effects models); * be able to produce, use and interpret the results from regression discontinuity designs; * be able to critically appraise the use of randomized controlled trials in social science; * understand when and why RCTs are necessary; * be aware of appropriate statistical methods in the analysis of trial data, including adjustment for covariates and subgroup analyses. Skills: * Ability to develop rigorous arguments through precise use of concepts and models; * ability to critically evaluate different research approaches and apply appropriate design principles and advanced quantitative techniques to particular disciplinary contexts; * ability to evaluate research findings produced by a range of different advanced empirical methods; * proficiency in using data from large scale surveys; * proficiency in construction of new data sets; * proficiency in descriptive and inferential statistics and ability to use, model and interpret multivariate statistical data and analysis using the range of techniques covered on the unit; * proficiency with using Stata to implement the various quantitative methods learned in the unit. Content: Topics to be covered include: advanced topics in regression (including limited dependent variable models: logit/probit/tobit), instrumental variables, quantile regression methods, difference-in-difference methods, regression discontinuity designs, longitudinal data model and analysis of randomized controlled trials. |
| Programme availability: |
XX50218 is a Designated Essential Unit on the following programmes:Department of Social & Policy Sciences
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Notes:
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