Introduction to survey data analysis using SPSS
By the end of the pathway, you should have learned:
- Key features of survey data including sampling, survey weights and missing data
- How to use SPSS (or the similar free software PSPP) to analyse survey data
- How to clean your data
- How to produce basic statistics, tables and visualisations from survey data precision and confidence intervals
- How to understand and work with longitudinal data
- How to use hierarchical files, complex sample design and analysing change over time
- The importance of data citation and how to cite data
Learn about how to find survey data from the UK and around the world, what you need to know about it before you can start analysing it, and how to produce simple tables and graphs for your research or reports.
Level: Introductory (no previous knowledge assumed)
Software: We use SPSS in the examples but you can do the examples in other statistical software. You can follow the module without having statistical software.
Dataset used: Quarterly Labour Force Survey, January-March 2015: Unrestricted Access Teaching Dataset
Certificate of completion available: Yes
Longitudinal studies collect data about individuals, households, businesses or any other unit of observation over time so they can be used for following changes over the life course. Learn what longitudinal studies are available, key features and issues with using longitudinal data and how to start some basic analyses.
Level: Introductory – but if you are new to surveys, we suggest you complete the surveys module first
Software: We use SPSS in the examples but you can do the examples in other statistical software. You can follow the module without having statistical software.
Dataset: UK Household Longitudinal Study (Understanding Society) (End user licence version)
Certificate of completion available: Yes
This guide introduces hierarchical datasets and how to understand and manipulate these.
Many social survey datasets use weights or weighting variables. This PDF guide explains the main reasons for using weights, how weight work and how to use weighting variables in statistical analysis.
This guide introduces the basics of sampling, complex sample design, clustering, stratification and using statistical packages.
This guide is an introductory guide to the main types of data available and some commonly-used methods for studying change over time quantitatively.
Experts from across the University of Essex, the Institute for Social and Economic Research, Understanding Society and the UK Data Archive come together to explain the importance of data citation.