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Unit information: Advanced Quantitative Methods for Social and Policy Research in 2021/22

Unit name Advanced Quantitative Methods for Social and Policy Research
Unit code POLIM0021
Credit points 20
Level of study M/7
Teaching block(s) Teaching Block 1 (weeks 1 - 12)
Unit director Dr. Mircea Popa
Open unit status Not open


POLI20001, SOCI20069 and one of POLI30011, SOCI30065, SPOL30031 or SPOL30032




registration on the MRes Advanced Quantitative Methods programme



School/department School of Sociology, Politics and International Studies
Faculty Faculty of Social Sciences and Law

Description including Unit Aims

The purpose of this unit is to introduce students to some of the higher-level quantitative methods, concepts and thinking that can be found in contemporary quantitative social science, with application to social and policy research, drawing upon the lecturers' own experiences of using the methods in their own research. Such topics may include discrete dependent variables, logistic regression, nonparametric estimation, postestimation, multilevel modelling, time-series, social network analysis, data reduction and reliability. The course also includes discussion of data collection, survey design and sampling, that will help students when thinking about their extended research projects.

The unit aims:

  • To expose students to some of the more advanced quantitative methods now found in the social sciences, going beyond traditional statistical inference and building upon regression
  • To give students experience of applying those methods through 'hands-on' learning
  • To encourage students to consider issues of research design and establishing robust answers to questions of association and causation
  • To help the students learn from real research being undertaken by members of the University of Bristol
  • To prepare the students for their extended research project using quantitative methods

Intended Learning Outcomes

At the end of this unit a successful student will:

-Be able to employ advanced statistical methods such as maximum likelihood estimation, time series estimation, and social network analysis to analyse social science data. -Be able to use statistical software such as R and Stata to implement the methods taught in the unit. -Be able to address data challenges such as missing data, data reduction and reliability, and sampling concerns. -Be able to engage with current applied research using the methods taught in the unit.

Teaching Information

The unit will be taught through blended learning methods, including a mix of synchronous and asynchronous teaching activities

Assessment Information

Portfolio of applied data analysis (100%), assesses all learning outcomes. Students will have a choice among several data analysis methods to use in the assignment, reflecting the methods taught in the unit. Assignment length: 3500-4000 words. Students will receive written comments on their work from the markers.


If this unit has a Resource List, you will normally find a link to it in the Blackboard area for the unit. Sometimes there will be a separate link for each weekly topic.

If you are unable to access a list through Blackboard, you can also find it via the Resource Lists homepage. Search for the list by the unit name or code (e.g. POLIM0021).

How much time the unit requires
Each credit equates to 10 hours of total student input. For example a 20 credit unit will take you 200 hours of study to complete. Your total learning time is made up of contact time, directed learning tasks, independent learning and assessment activity.

See the Faculty workload statement relating to this unit for more information.

The Board of Examiners will consider all cases where students have failed or not completed the assessments required for credit. The Board considers each student's outcomes across all the units which contribute to each year's programme of study. If you have self-certificated your absence from an assessment, you will normally be required to complete it the next time it runs (this is usually in the next assessment period).
The Board of Examiners will take into account any extenuating circumstances and operates within the Regulations and Code of Practice for Taught Programmes.