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XX50219: AQM 2 - Advanced modelling techniques for social sciences

Follow this link for further information on academic years Academic Year: 2018/9
Further information on owning departmentsOwning Department/School: Faculty of Humanities & Social Sciences (units for MRes programmes)
Further information on credits Credits: 6      [equivalent to 12 CATS credits]
Further information on notional study hours Notional Study Hours: 120
Further information on unit levels Level: Masters UG & PG (FHEQ level 7)
Further information on teaching periods Period:
Semester 2
Further information on unit assessment Assessment Summary: CW 50%, EX 50%
Further information on unit assessment Assessment Detail:
  • Exam (EX 50% - Qualifying Mark: 40)
  • Essay (CW 50% - Qualifying Mark: 40)
Further information on supplementary assessment Supplementary Assessment:
Like-for-like reassessment (where allowed by programme regulations)
Further information on requisites Requisites:
Further information on descriptions Description: Aims:
This is an advanced level quantitative methods course designed to equip students with a range of technical skills covering the a number of major techniques of data analysis used in social sciences but not covered in XX50218 (AQM 1 - Experimental and Quasi-experimental Quantitative Methods in Social Science). 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 competence 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 structural equation models;
* understand and be able to implement path analysis;
* understand and be able to implement social network analysis;
* understand and be able to implement latent class models;
* understand and be able to implement linear mixed models;
* understand and be able to implement meta analyses.


* 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.

Topics to be covered include: structural equation models, path analysis, social network analysis, latent class models, linear mixed models and meta analysis techniques.
Further information on programme availabilityProgramme availability:

XX50219 is a Designated Essential Unit on the following programmes:

Department of Social & Policy Sciences
  • THXX-AFM54 : MRes Advanced Quantitative Methods in Social Sciences
  • THXX-AFM76 : MRes Advanced Quantitative Methods in Social Sciences
  • THXX-APM54 : MRes Advanced Quantitative Methods in Social Sciences