Abstract copyright UK Data Service and data collection copyright owner.
The aim of this project was to make easier-to-handle teaching datasets from Understanding Society, building a core of common variables from the first three waves but including some other wave-specific information from each wave. The richness of the data, including the combination of ratio/interval data as well as categorical/ordinal data, makes for an effective dataset from which to teach quantitative methods of all kinds. A distinctive feature is the provision of datasets in native R format in addition to those in a statistical format. The documentation for the 'parent' Understanding Society dataset (SN 6614 at the UK Data Service) is the definitive guide to the variables, sampling, etc. The dataset was compiled under the ESRC-funded Understanding Society Through Secondary Data Analysis: Quantitative Methods over the Undergraduate Life Course award. This project aimed to enhance the capacity of social science undergraduates to understand and use numeric data in their studies, by generating teaching-ready datasets based on Understanding Society. It also aimed to create associated digital resources that will be available for other students to use; to increase the amount of work using secondary data at the undergraduate level and to underline the relevance of research methods to the study of social sciences. As part of the award, a programme of new courses was planned, taking undergraduate students from their first year through to their final year. This new approach aimed to provide a solid foundation for employability and future careers using quantitative skills (whether in the public sector, in academia, or elsewhere).
Main Topics:
Extraction of data from main Understanding Society study, including sex, age, residential history, country of birth, citizenship, ethnicity, languages spoken, religion, marital history, families, health, employment, environmental conservation habits, income, political affiliation and awareness, education, responsibilities for household tasks, television viewing and newspaper readership.
No sampling (total universe)
Transcription of existing materials
