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Applied Social Data Analysis in R

Classes

There are no classes currently available for registration.

Overview

Year Of Entry
2023-24
Fees
£818

Our Applied Social Data Analysis in R short course is ideal if you have a background in data analysis and/or statistics but no prior experience of programming. R is a powerful programming language widely used by data analysts and data scientists and known for its extensive libraries and strong community support.

We plan to cover:

  • practical R programming
  • inferential statistics refresher: distributions and bivariate relationships
  • data management and data visualisation
  • linear regression deep dive: basic concepts, estimation, goodness of fit, diagnostics
  • extending the linear regression framework.

This postgraduate-level short course will appeal if you are a professional in a public sector or nonprofit organisation, or work in research, including social research and/or programme evaluation. It can also make a valuable contribution to your Continuing Professional Development (CPD).

Assessment is via two take-home/post-lab replication exercises (20% each) and a take-home examination (60%).

15 credits at level 7

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  • Entry requirements

    Entry requirements

    You must have an undergraduate degree, which may be in any discipline, and some experience of data analysis and bivariate statistics (such as correlations, t-tests).

    As part of the enrolment process, you may be required to submit a copy of a suitable form of ID.

    International students who wish to come to the UK to study a short course can apply for a Visitor visa. Please note that it is not possible to obtain a Student visa to study a short course.

  • How to apply

    How to apply

    You register directly onto the classes you would like to take. Classes are filled on a first-come, first-served basis - so apply early. If you wish to take more than one short course, you can select each one separately and then register onto them together via our online application portal. There is usually no formal selection process, although some modules may have prerequisites and/or other requirements, which will be specified where relevant.

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