Information regarding our 2022/23 admissions cycle

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BA Criminology and Data Analytics / Course details

Year of entry: 2022

Course description

On the BA Social Sciences in Criminology and Data Analytics course, you learn theories about the nature and determinants of crime, but also how to translate these theories into empirical questions that can be studied using real-life data.

Specifically, you learn data analytic and data science techniques to evaluate the effectiveness of anti-crime policies, understand criminal behaviour, predict and classify criminal phenomena and describe and analyse networks of relationships between criminals, criminal organisations and society.

By completing the core and optional units, you will gain sought after skills, including:

  • how to collect, describe and visualise data;
  • how to build quantitative models to explain phenomena;
  • how to quantitatively evaluate the effectiveness of policies;
  • how to map and analyse complex social networks;
  • how to implement key machine learning algorithms;
  • how to implement data analytic techniques and data science algorithms using statistical software including R, as well as proprietary packages such as SPSS.

The pathway emphasises the application of modern data analytic methods to real-life problems. Although, you will have the opportunity to learn some of the underlying theory to progress further in your career to more advanced postgraduate courses and more challenging scenarios in policy and industry.

Special features

Professional experience opportunity

You have the option of extending your studies and boosting your employability through a paid professional placement year.

You can apply in Year 1 or 2, complete your placement in Year 3, then return to University for Year 4.

The degree title will include 'with Professional Experience', giving you the added advantage of relevant work experience when entering the competitive graduate jobs market.

Study abroad

You can apply in Year 1 to spend a semester abroad in Year 2. If you are successful, you will put together a package of course units at your host university in consultation with your Academic Exchange Advisor in Manchester

Paid placement opportunity

You can apply for a paid Q-Step internship during the summer between the second and third year of your course.

Teaching and learning

Course units feature formal lectures supported by smaller tutorials or seminars where you explore the contents of lectures and recommended reading in greater depth.

Tutorials and seminars are key to improving your written and oral communication skills through group discussions, essay-writing, and presentations.

You are assigned an Academic Advisor who can advise you on selecting course units and career opportunities.

Coursework and assessment

The range of methods is designed to promote in-depth learning and understanding, including:
  • essays, coursework and other mid-term evaluations;
  • dissertations;
  • presentations and group projects;
  • exams.

Course content for year 1

Year 1 gives you a broad introduction to the Social Sciences.

Students on the Data Analytics pathway must take the core unit SOST10021 'Measuring Inequalities'.

Course content for year 2

In Year 2, you begin to specialise.

Students on the Data Analytics pathway take two core units:

  • SOST20022 Essentials of Survey Design and Analysis.
  • SOST20142 Applied Statistics for Social Science.

Course content for year 3

In Year 3, you pick your final areas of specialisation.

Students on the Data Analytics pathway take the core unit SOST30031 'Answering Social Research questions with Statistical Models'.

In addition, students are encouraged to take:

  • SOST30172 Quantitative Evaluation (of policies, interventions and experiments).
  • SOST30036 Data Science Modelling.

Plus, at least one of:

  • SOST30022 Advance Social Network Analysis.
  • SOST30012 Theory and Method in Demography.

Course content for year 4

If completing a year professional placement, you will take the Year 3 course content in Year 4.

Disability support

Practical support and advice for current students and applicants is available from the Disability Advisory and Support Service. Email: dass@manchester.ac.uk