Book contents
- Frontmatter
- Contents
- Acknowledgements
- Introduction: Types of research
- Part 1 The research process
- Part 2 Methods
- 9 Introducing research methods
- 10 Desk research
- 11 Analysing desk research
- 12 Collecting quantitative data
- 13 Analysing quantitative data
- 14 Collecting qualitative data
- 15 Analysing qualitative data
- 16 Sources of further reading
- Appendix The market for information professionals: A proposal from the Policy Studies Institute
- Index
12 - Collecting quantitative data
from Part 2 - Methods
Published online by Cambridge University Press: 09 June 2018
- Frontmatter
- Contents
- Acknowledgements
- Introduction: Types of research
- Part 1 The research process
- Part 2 Methods
- 9 Introducing research methods
- 10 Desk research
- 11 Analysing desk research
- 12 Collecting quantitative data
- 13 Analysing quantitative data
- 14 Collecting qualitative data
- 15 Analysing qualitative data
- 16 Sources of further reading
- Appendix The market for information professionals: A proposal from the Policy Studies Institute
- Index
Summary
For many people, collecting quantitative data is the core of social research. Types of quantitative techniques are the things that first come to mind when people think of social research – techniques such as self-completion questionnaires and interview surveys. They are all founded on the principle that you can generate information about the characteristics of a group by collecting data from a subset of that group.
This principle was developed first by researchers in the natural sciences. They carried out experiments and measured the results. The experiments were then repeated many times until the researchers could be sure that the results they obtained were not the product of random chance but were characteristic of the subjects or objects they were studying. This approach has been subsequently adapted by social scientists and it underpins all quantitative methods.
Sampling
Let's face it, sampling is difficult. The basic principle is straightforward: you take a sample from a large group, look in detail at that sample and then infer the characteristics of the whole group from those of the sample. Of course, it is not quite that simple. You can never be sure that the sample has the same characteristics as the group – they probably do, but you cannot be certain. So you have to allow for that degree of probability.
Sample size
You need a sample that is big enough to represent all the characteristics of the larger group. In part, this depends on the relative size of the group and the sample you select. Let us suppose that you are trying to measure the proportion of people in the population who have brown hair and blue eyes. You walk down the street and the tenth person you meet has brown hair and blue eyes. Can you infer from this that ten per cent of the population have brown hair and blue eyes? Probably not.
So you walk on and look at 100 people. Of these, eight have brown hair and blue eyes. So, is the proportion eight per cent? Well possibly, but to be a little more certain you carry on walking until you have passed 1000 people. By now you have counted 78 people with brown hair and blue eyes. You can fairly confidently say that about eight per cent of the population have the brown hair–blue eye combination.
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- Information
- How to Do ResearchA practical guide to designing and managing research projects, pp. 115 - 132Publisher: FacetPrint publication year: 2006