Checking for bias in data collection |
Data from experiments, survey questionnaires and interviews can be influenced by either the context of the study, the respondents themselves, or the researcher. The term "bias" is often used in this context, but the term is ambiguous. Technically meaning "leaning" in one direction, it is often used to refer to respondents or researchers having pre-conceived ideas or an ideological disposition. What we mean here by bias is anything that can "contaminate" the picture you are trying to get of either subjects' behaviour or their attitudes and beliefs.
Here is a checklist for the researcher to check for factors which could be influencing or contaminating the data: (adapted from Plummer: 1983)
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It's important to understand that bias is inevitable and normal. The problem is not the presence of biasing factors, but that the writer seems unaware of them, and interprets interview or questionnaire data as a "true account" of reality. This can lead to exaggerated claims based on the data.
Go to Values and Stance (Academic Writing) for more on this.