Skip to main content

Intermediate Quantitative Social Research - Non-credit bearing

Classes

There are no classes currently available for registration.

Overview

This is a non-credit bearing course but can also be taken as a credit bearing course.

Discover the difference between our credit bearing and non-credit bearing courses.

This Intermediate Quantitative Social Research short course introduces you to quantitative research methods, through hands-on experience using R computer software. You will be introduced to survey methodology and experimental research designs and are encouraged to conduct your own projects using quantitative data.

We will spend the first five weeks of Intermediate Quantitative Social Research refreshing the material covered in our Introduction to Quantitative Social Research short course, such as sampling, descriptive statistics, inferential statistics and OLS regression. We will then move on to considering more advanced techniques such as logistic regression, time series analysis, the study of panel data and multi-level modelling (the precise combination will vary from year to year).

We plan to cover the following content:

  • Descriptive statistics in R
  • Data visualisation in R
  • Analysing survey data
  • Fitting and interpreting OLS regression models
  • Fitting and interpreting logistic regression models
  • Fitting and interpreting mixed effects regression models
  • Model comparison and model diagnostics
  • Formulating and addressing quantitative research questions
  • How to read and evaluate quantitative research papers
  • How to write a quantitative research paper

This short course is taught at postgraduate-level and is ideal for professionals in the social sciences or those with an undergraduate background in this area looking to enhance their research skills and gain hands-on experience with quantitative data analysis in R.

This course is non-credit bearing, so carries no credit points.

  • Entry requirements

    Entry requirements

    Most of our short courses have no formal entry requirements and are open to all students.

    You should already be familiar with basic statistics terms (mean, median, variance, correlation) and mathematical terms relating to linear regression (intercept, slope). Prior experience fitting a linear regression model (in any statistical software) is an advantage. Prior experience with R software is not required.

    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.