The SSH Training Discovery Toolkit provides an inventory of training materials relevant for the Social Sciences and Humanities.
Use the search bar to discover materials or browse through the collections. The filters will help you identify your area of interest.
|R for Reproducible Scientific Analysis||
An introduction to R for non-programmers using gapminder data
The goal of this lesson is to teach novice programmers to write modular code and best practices for using R for data analysis. R is commonly used in many scientific disciplines for statistical analysis and its array of third-party packages. We find that many scientists who come to Software Carpentry workshops use R and want to learn more. The emphasis of these materials is to give attendees a strong foundation in the fundamentals of R, and to teach best practices for scientific computing: breaking down analyses into modular units, task automation, and encapsulation.
Spanish version available here
Github repository available here
|Cross sectional and longitudinal survey data||
This is an introductory guide to the main types of data with a time element. The guide is a brief overview of key elements in need of consideration when using these types of data. It also covers data availability and some commonly used methods for studying change over time quantitatively.
|What is complex sample design?||
This guide covers the basics of sampling as well as other related topics such as clustering, stratification and weighting.
|What is weighting?||
This guide explains the main reasons for using weights, how weights work and how to use weighting variables in statistical analysis.
|Using survey data||
This guide aims to help researchers utilise extensive survey data available. In particular, this guide is designed to support those starting small research projects, especially students doing dissertations.
The guide includes materials to read, worksheets for getting started and questions to think about and answer.
|Mapping Census Data in QGIS||
This guide will cover how to map census data in QGIS. The example used in this guide creates a choropleth map showing the percentage of males who work in the manufacturing service using the QGIS package.
|Mapping Census Microdata using R||
This guide aims to show the strength of using Census Microdata for a variety of research purposes, via a worked example taken from real-life research. This guide assumes some familiarity with microdata, mapping and statistical software.
|Quantitative methods e-books||
These quantitative methods e-books and accompanying quizzes are for direct use in teaching students or for self-study. They aim to build skills in quantitative methods and statistical software and use the Living Costs and Food Survey.
Using SPSS, lecturers and students can utilise both the practical and quiz elements of each e-book topic. Topics include examining variables, correlations, regression and multiple regression.
The e-books have been developed through a collaboration of the UK Data Service, National Centre for Research Methods (NCRM), and the Centre for Multi-Level Modelling at the University of Bristol and were created using the StatJR software based on original outputs from the project Using Statistical E-books to teach undergraduate students quantitative methods and statistical software funded by the British Academy.
|UK Business Data User Conference 2021||
The UK Data Service and the Office for National Statistics (UK) held a business data conference in 2021. This resource provides all slides, recordings and other useful materials from the conference.
The conference included a mixture of presentations from the Office for National Statistics (ONS), UK Data Service, and researchers who have used data from the UK Surveys covering the areas of business, industry and trade.
|Linking external business data to ONS business data||
The UK Data Service is able to assist researchers wishing to link external business data to ONS business data in the Secure Lab. This guide provides all the information needed to guide users wishing to link external business data to ONS business data.