What is Social Statistics?
Social statistics is the use of statistics to study human behaviour and social environments. Social statistics data is information or knowledge on an individual, object or event.
Statistics are numbers, summaries of patterns and can also be probabilities.
Statistical analysis can include the design and collection of data, its interpretation and presentation.
Social statistics and quantitative data analysis are key tools for understanding society and social change. We can try to capture people’s attitudes and map patterns in behaviour and circumstances using numbers and also describe how people and populations change.
What is data?
Data can be numerical values or text, sounds or images, memories or perceptions.
Often the concept of data suggests information that has been through some kind of processing and having a structure. However, many examples of new types of data have very different and often unstructured formats; for example, millions of tweets or thousands of PDFs of public documents.
Huge quantities of data on people, organisations and social groups are collected each day, across the world. As social statisticians, it is our role to analyse and make sense of the huge volumes and sources of data using hypothesis-driven social research.
Social statistics are a means of investigating and testing research questions and policy impacts across different areas of people’s lives. These observations help our understanding of society, research questions include:
- How are populations growing?
- Are wealthy people happier?
- Is society becoming more tolerant of diversity?
- How do people cope with financial hardship?
- Do people with higher qualifications earn more?
- Does volunteering increase your sense of wellbeing?
Social statistics are a means of investigating and testing research questions and policy impacts across different areas of people’s lives.
Social statistics in the real world
The United Nations Social Statistics Division analyses differences among social groups and countries covering such issues as housing, health, education, conditions of work and employment.
It pays special attention to the study of conditions of special population groups, including children, the elderly, the unemployed, and people with disabilities.
Compare the facts
Social statistics are also used to compare data from before and after a policy intervention.
For example, we need statistics to measure poverty in the first place and we then may want to assess the impact and costs of a policy providing financial support to families living in poverty.
Patterns and relations
Statistical analysis techniques can be used to explore patterns and underlying relationships in data sets, such as:
- in relation to people’s responses to multiple questions in a survey;
- to take account of aspects of people's circumstances such as the unemployment rates of where they live; or
- the educational standards of the class and/or school they are studying in;
- change can also be measured through longitudinal surveys where people are interviewed at different points during their lives.
Statistical testing and modelling techniques can be used to generalise from small samples to larger populations, for example:
- predicting the outcome of an election;
- attitudes towards the economy in a country.
Probability tests can be used to identify the key factor(s) associated with a particular outcome or behaviour. For example, are older people more likely to be worried about being a victim of crime than younger people once you have taken account of their family status, education, job and the type of area they live in?
Statistics and employability
Skills in analysing data and using statistics are vital across the research areas of population change, health, family life, the economy, well-being, education, employment, law and criminal justice, housing and civic participation.
Even if you are primarily using qualitative data, skills in understanding the bigger picture can add to the explanatory power of your empirical research.
For example, a study of long-term unemployment based around qualitative interviews can be strengthened by a quantitative summary of the patterns and duration of unemployment at the local, national land international level and how these patterns have changed over time.
- The Guardian: Data blog
- Radical Statistics - Using statistics to support progressive social change
- Ben Goldacre’s Bad Science