Welcome to the learning resources page for the University of Exeter’s Q-Step Centre

Here, you will find a range of teaching materials that have been developed by members of the Q-Step Centre. If you have any questions, please contact l.brace@exeter.ac.uk or qstep@exeter.ac.uk. Details of Q-Step workshops and events can be found at https://socialsciences.exeter.ac.uk/q-step/events.

Computational methods

Python

Below are a series of resources for learning the Python generic programming language. Most of these are tailored towards those who wish to learn the language for data analytics purposes, but many of the skills and methods discussed in these materials are transferable.

Introduction to Python

Practical Introduction to Python - pdf

Practical Introduction to Python - PowerPoint

Data analysis and visualisation with Python

Data Analysis and visualisation with Python - pdf

Data Analysis and visualisation with Python - PowerPoint

Introduction to Jupyter notebooks

Jupyter notebooks are a fantastic way to learn how to code in Python. They enable instructor to essentially build interactive textbooks. Jupyter is installed as part of the Anaconda distribution of Python. Instructions for downloading and installing this can be found in the following document:

How to install the Anaconda distribution of Python - pdf file

The following serves as an introduction to Jupyter notebooks: Introduction to Jupyter notebooks workshop materials - zip folder

The following file covers the content that is covered in the Introduction to Python and Data Analysis with Python workshops above, but allows for the interactivity of the notebooks. Do note that you will need Jupyter installed before you can run the notebook, see the above zip folder.

Introduction to Python for Data Analysis Hupyter notebook - ipynb

Python for social scientists

Python for social scientists workshop materials - zip folder

Text data analysis in Python

Text data analysis in Python workshop materials - zip folder

Introduction to GIS with QGIS

A geographic information system (GIS) is a system designed to allow researchers to capture, store, manipulate, analyse, manage, and present spatial or geographic data. This workshop will introduce attendees to the introductory principles of GIS and how to use the Python-based QGIS for research purposes.

Introduction to QGIS - weblink

Open-Source Intelligence (OSINT)

Introduction to Open-Source Intelligence (OSINT)

This is an Introduction to Open-Source Intelligence (OSINT). It will cover some broad themes of what OSINT is and what it is not, as well as some thoughts on the future of OSINT.

This will be an applied workshop where you will be introduced to some tools for basic OSINT research in regards to the surface web and social media intelligence. No prior knowledge of open source is required.

Adina Pintilie is a proud alumna of Q-Step’s BSc Politics and IR programme. She holds an MA in Applied Security and Strategy and is an Open Source Intelligence Researcher at Ridgeway Information. She has previously worked on academic research projects focusing on the uses of social media and the main polling division of the European Union. Currently, she works with a major United Nations agency, the UK government and the National Police Chiefs’ Council on implementation of OSINT skills and methodologies

Introduction to OSINT slides - pdf

R

Below are a series of training resources for learning the R statistical programming environment.

Introduction to R

Introduction to R - pdf

Introduction to R - PowerPoint

Previous introduction to R workshop This workshop provides an introduction to basic programming notions and their application in R. We will start with an overview of R objects and their attributes. You will then learn how to import data into R and perform simple data manipulations. Finally, we will go over a few simple examples of data analysis and visualization and introduce some of the most commonly used R packages. We will be using RStudio, a user-friendly interface to R.

Previous Introduction to R workshop from 2016 - weblink

Previous Introduction to R workshop from 2016 materials - zip folder

Data analysis in R

Building upon the “Introduction to Programming in R” session, this workshop provides a brief introduction to major data analysis topics and their implementation in R. Covered topics include: probability distributions, regression analysis, models for binary and categorical data.

Data analysis in R workshop - web link

Data analysis in R workshop materials - zip folder

Introduction to Bayesian analysis with R - 11/05/2020

One of the advantages of Bayesian analysis is its great flexibility with respect to the functional form of the model. To take full advantage of this flexibility, the analyst need to know how to write code for Stan, JAGS, BUGS or a similar sample.

In this workshop, we will learn the basics of modelling with JAGS (“Just Another Gibbs Sampler”) and R. As an application, we will work through the estimation of simple multi-level models and models with measurement errors.

Introduction_to_Bayesian_analysis_with_R_slides.pdf - pdf

Introduction_to_Bayesian_analysis_with_R_resources - zip folder

Bayesian analysis with JAGS/Topics in Bayesian analysis with R - 12/05/2020

One of the advantages of Bayesian analysis is its great flexibility with respect to the functional form of the model. To take full advantage of this flexibility, the analyst need to know how to write code for Stan, JAGS, BUGS or a similar sample.

In this workshop, we will learn the basics of modelling with JAGS (“Just Another Gibbs Sampler”) and R. As an application, we will work through the estimation of simple multi-level models and models with measurement errors.

Introduction_to_JAGS_with_R_slides - pdf

Introduction_to_JAGS_with_R_resources - zip folder

Data visualisation in R

An introduction to the common approaches to data visualisation in R, including line / bar charts, scatterplots, histogram and density plots in base R and using the ggplot2 package. We will also discuss the aesthetics, geoms and faceting systems in ggplot2. Please bring your own laptop with R, RStudio, and the following packages installed: “tidyverse”, “titanic”.

Data visualisation in R workshop materials - zip folder

Data management in R

An introduction to some of the most popular functions and packages for data management/manipulation including fast data cleaning, recording a number of variables simultaneously, aggregating or summarising data by groups, merging tables, reshaping tables. Using an example data set provided on the spot, we will go through (s/t)apply functions, and functions provided by the dplyr package and the data.table package.

Data management in R workshop materials - zip folder

Presenting and visualising regression results in R

This workshop introduces various ways of automating regression output from Stata and R. It starts by covering ways how to automate table creation for Latex and Word and then proceed to visualising marginal effects and predicted probabilities from linear and binary dependent variable regressions and finally discuss visualisation of interaction effects.

Presenting and visualising regression results in R - zip folder

Social network analysis in R

The workshop provides an introduction for beginners to Social Network Analysis. It gives an overview of key concepts needed to design research that looks at social relations (networks) that connect individual units (actors), so that students can apply social network analysis to their own research. The workshop focuses on the description and visualisation of social network data, looking at structural properties of a network, as well as ideas of centrality in the network. To understand the SNA perspective, practical examples are given from academic literature, illustrative graphics from the media, and source material visualised through R.

Social Network Analysis in R workshop materials - zip folder

Collecting social media data in R

This workshop provides an introduction to the main methods used to access download and store social media data. You will learn how to use Twitter’s APIs to collect past and future data, and how to access Facebook data using its Graph API. Basic knowledge of programming in R is required, and participants are encouraged to attend the “Introduction to Programming in R” workshop first.

Collecting social media data workshop materials - zip folder

Geographical and Place-based dependence in multilevel models

Session run by Dr Levi Wolf (University of Bristol) as part of the Q-Step Seminar Series in the 2019/20 academic year. Held at the Clayden Computational Lab, Streatham Campus, University of Exeter on Friday 7th February 2020.

Geographical and Place-based dependence in multilevel models - web link

SPSS

Introduction to SPSS

The Q-Step workshop offers a brief guidance on how to get started with SPSS. It reflects on the drawbacks and benefits of the software and explains how to prepare your data to use in SPSS. The workshop then moves on to demonstrate how you can describe the data in SPSS using the 2010 British Election Study data. There are no pre-requisites for taking the workshop, and no prior knowledge of data analysis is assumed.

Introduction to SPSS workshop materials - zip folder

Intermediate SPSS

This workshop introduces you to the basics of statistical analysis using SPSS focusing on cross-tabulations and correlations in particular. The workshop is taught at the intermediate level and requires basic knowledge of SPSS or the attendance of SPSS Beginners Workshop.

Intermediate SPSS workshop materials - zip folder

SQL

Introduction to SQL

Introduction to SQL for Data Management - pdf

Introduction to SQL for Data Management - PowerPoint

Nvivo

The workshop will introduce and provide hands on applications of various techniques of content analysis especially focusing on the analysis of texts. It starts from outlining the key concepts, defining units of analysis and understanding measurement techniques and theoretical approaches. It then moves on to reviewing applications of content analysis to Social Sciences data (e.g., parliamentary records, political manifestos, policy documents). Finally, participants will be provided with textual data to practice the content analysis techniques.Feel free to bring your own documents (any type of text in digitised, preferably .txt, format) to the workshop

Nvivo workshop materials - zip folder

Quantiative research methods

How to read an empirical paper

Reading empirical articles can be intimidating. The new reader may be daunted by technical jargon, complex methodological procedures and statistical analysis. This workshop will guide you through a process to make sense of the typical analysis in an empirical study.

How to read an empirical paper workshop - weblink

How to read an empirical paper workshop supporting materials - zip folder

Writing a quantitative dissertation

These resources are aimed at Q-Step students in their final year of study that are preparing to write a quantitative dissertation. The recorded workshop and the session slides introduce students to the core aspects of writing a “quantitative” dissertation, including several “tips and tricks” regarding research design and the overall dissertation structure.

Q-Step How to write a quantitative dissertation handbook - pdf

Q-Step Disseration workshop 2017 - weblink

How to write a quantitative dissertation additional resources

Politics through the life course

Politics through the life course workshop materials - zip folder

Qualitative research methods

Survey design

Qualtrics

Using Qualtrics to design and field surveys and survey experiments.

Introduction to Qualtrics Workshop - web link

Introduction to Qualtrics Workshop Supporting materials - zip folder