Take the following data:
- The proportion of households falling below society's minimum standards has doubled since 1983
- 5 million more people live in inadequate housing than in the 1990s
- 11% of households can't heat their homes adequately today up from 5% in 1983 and 3% in 1999
These statistics, taken from the Poverty and Social Exclusion Study, UK provide a picture of social life in the UK that seems immediately understandable. How is this understanding conveyed?
First, each of the statements includes some reference to a change in social conditions in relation to an earlier time period. This provides an immediate context against which to understand the meaning behind the figures that are presented.
Second, we are provided with clear indicators of poverty, in this case: inadequate housing, the ability for people to heat their homes and minimum standards of living. See the Poverty and Social Exclusion site for more detail.
In examples such as this, statistics can provide a useful guide for understanding the quality of social conditions in which people live, and they begin to tell us a story or paint a broad picture of social life. However, sometimes statistics can be difficult to understand.
- How can we understand what a statistical figure is really saying?
- Are there statistics we can trust and ones we can’t, and how do we tell the difference?
- Are there limitations to the knowledge that we can gain from statistics?
Moreover, you also need to consider whether there are any limitations of the data you are looking at. This might include: whether the number of cases that the data draws upon are sufficient to generalise; if it is survey data, you should consider the way questions were asked; and if you’re looking to compare data over time, you need to make sure that the data sources remain reliable and stable.
For example, when looking at a dataset that has been collected in different time periods or over a lengthy space of time, there can be difficulties of defining measures and making comparisons. The way a particular measure is calculated may change or alternatively there may be changes to the living conditions in a local area that are not reflected in the statistics.
When levels of household income are measured, for instance, there are two ways in which the number of households counted beneath a threshold can change. Firstly, the threshold may stay the same, but households may become poorer.
Secondly, a household may remain the same, but the threshold criteria may increase. Thus, when working with an existing data set it is important to check that the threshold criteria remains the same across time periods for the particular indicator you are interested in.
The data and how to use Postcode Patterns
We've launched Postcode Patterns, a way to discover and compare data from different neighbourhoods covering income, education, older people, community and health.
Using the Borough of Milton Keynes (the home of The Open University headquarters) as a case study, we present and examine some local social statistics in order to begin to answer some of these questions and to give you more confidence in reading and interpreting statistics. Postcode Patterns will also provide you with some basic skills and tips for accessing data.
This site presents some local social statistics for Milton Keynes, drawn from MKi Observatory. This is a web-based data resource which anyone can access in order to share, map and visualise data.
In Milton Keynes, the local council use this data to better understand some of the social issues that affect residents. The data is also used by other organisations who are interested in learning more about the way social issues affect different communities in different ways and the way these change over time.
Milton Keynes Council uses the data to produce a ‘social atlas’, which helps them to gain understanding of:
- the most significant social inclusion issues
- geographic concentrations of need
- the relative severity of social exclusion compared with other areas and the national picture
- geographic areas and issues where development of services and initiatives might be focused
- where changes are occurring
The data we have drawn on to build this website aims to measure levels of deprivation. Certain indicators (e.g. housing benefit, education levels, adult education, and incidents of crime) tend to be utilised by various policy makers and councils as measurable indicators of deprivation.
While the statistics provide one way of drawing a picture of a particular area, town or city, there are other ways of understanding, measuring and studying social conditions.
Working through Postcode Patterns, we will consider ‘statistical pictures’ of areas of Milton Keynes, but we will also consider some qualitative or descriptive pictures of areas of Milton Keynes, which often contrast with what the statistical information suggests.
The data on this site are drawn from a range of local sources, including the Census. For the complete data sets on which the data visualisations on this site have been based, use the 'Get the Data' button.
Alternatively, if you’re not from Milton Keynes, you might want to look at data that is relevant to your local area—ask your local council where you can find social data sources that are relevant to your area. Most councils will maintain similar data sets and can be accessed for free.
We hope you find Postcode Patterns an interesting and enjoyable way to explore statistics.