BA History and Sociology

Basic knowledge of statistical analysis.

The unit aims to:  

Introduce a toolbox for empirical statistical investigation of theories on relations between social units. 
Introduce the practical issues involved in managing and analysing network data. 
Provide a concept- and research-driven perspective on everyday observables and the skills and knowledge to solve analytical puzzles in a wide array of applied contexts. 
Give students a working handle on the basic network analysis tools. 
Foster familiarity with analytical tools and methods at a level that enables students to further their skills in relevant areas. 
Offer a statistical analytical framework for critical appraisal of quantitative statements in networks and related areas.

The course involves lectures and computer workshops. The lecture component provides theoretical and methodological frameworks for learning about the analysis of social network data and the key pathways from theory to subjecting research questions to empirical scrutiny. The workshops are linked to the lectures and serve to give a concrete and hands-on perspective on the material taught. Furthermore, the workshops give students training in specific methodologies and embed practical skills. The workshops have an immediate goal of equipping students with the necessary skills and knowledge to complete the assignment. Canvas resources are used to enable students to access teaching data and data sources. Students are also provided with video materials of lectures and software tutorials. 

Understand the empirical requirements and evidence needed for drawing conclusions about complex social processes involving network structures. Operate with fundamental concepts in network analysis, both theoretical and technical.

Relate concepts such as micro-macro, self-organisation, structuring mechanism, and emergence to specific predictions and hypotheses for observables on network data. Choose the appropriate network-analytical approach for a particular set of relevant research questions.  

Manage social network datasets and analyse network data with dedicated network-analytical software.  
 

Visualise, describe, and report the results of social network analysis, drawing conclusions about related social processes.  
 

Apply essential network-analytical concepts.

Handle network data, interpret analytical results, and report them.

Written assignment (essay) 100%

The word count must not exceed 2000 words. The essay must include a (1) network visualization and tables with (2) descriptive statistics, (3) statistical model and goodness of fit test, (4) interpretations of 1-3.

All Social Statistics courses include both formative feedback - which lets you know how you're getting on and what you could do to improve - and summative feedback - which gives you a mark for your assessed work. 

Borgatti S., Everett M, Johnson J. (2018). Analysing Social Networks 2nd Ed, Sage, London 

Hanneman R.A. and Riddle M. (2005). Introduction to Social Network Analysis. Available at https://faculty.ucr.edu/~hanneman/nettext/ 

Lusher,D., Koskinen, J., and Robins, G. (2013). Exponential random graph models for social networks: Theory, methods and applications. Cambridge University Press 

Robins, G. (2015). Doing Social Networks Research: Network Research Design for Social Scientists. Sage.  

Scott, J. (2000) Social Network Analysis: A Handbook, London, Sage 

Wasserman, S. and Faust, K. (1994) Social Network Analysis, Cambridge University Press 

Online Resources:

Mitchell Centre www.ccsr.ac.uk/mitchell  

Methods@Manchester www.methods.manchester.ac.uk/  

Tuition fees for home students commencing their studies in September 2027 will be £10,050 per annum. Tuition fees for international students will be £29,200 per annum.

For general information please see the undergraduate finance pages.

All students should normally be able to complete their programme of study without incurring additional study costs over and above the tuition fee for that programme. Any unavoidable additional compulsory costs totalling more than 1% of the annual home undergraduate fee per annum, regardless of whether the programme in question is undergraduate or postgraduate taught, will be made clear to you at the point of application. Further information can be found in the University's Policy on additional costs incurred by students on undergraduate and postgraduate taught programmes (PDF document, 91KB).

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As an international student you may be eligible for our Global Futures Scholarships . This is open to students starting their studies in September 2026.