12.3 Bias in data collection
If you ‘hand pick’ your study subjects when you are collecting data, then it is likely that you are introducing bias in your study. Bias in data collection is a distortion which results in the information not being truly representative of the situation you are trying to investigate. Sources of bias can be prevented by carefully planning the data collection process.
Can you think of a way that bias might be accidentally introduced into a survey?
In interviews, when you are asking questions, it is important not to prompt respondents into giving particular answers because this could introduce a source of bias.
To avoid bias you need to collect data as objectively as possible, for example, by using well-prepared questions that do not lead respondents into making a particular answer. If you are selecting a sample of people for your research (i.e. not including everyone) then you must ensure the sample is representative of the population or group you are studying. If you are using volunteers to help in collecting data, you should ensure that everyone is collecting and recording data in the same way and that they all understand the need to avoid prompting the respondents to particular answers.
Once you have collected your data, you are ready to start processing and analysing it.