Poor technique in surveying or choosing a sample can lead to incorrect conclusions about the population that are generally referred to as bias.
Sampling Bias: bias in the methods used in selecting the sample
- Convenience Sampling: subjects are selected because of their convenient accessibility and proximity to the researcher
- Judgement Sampling: an individual or organization that is usually considered an expert in the field being studied chooses the individuals or group of individuals to be used in the sample
- Size Bias: one particular subgroup in a population is likely to be over-represented or under-represented due to its size
- Voluntary Response Bias: occurs when sample members are self-selected volunteers, because the people who choose to respond most likely feel strongly about the issue
- Non-response Bias: occurs when respondents differ in meaningful ways from nonrespondents
- Questionnaire Bias: occurs when the way in which the question is asked influences the response given by the individual
- Incorrect Response Bias: occurs when an individual intentionally responds to a survey with an untruthful answer
Example: You are assisting with a study attempting to determine the satisfaction of school communication with students who speak a second language at home. The plan is to send home a questionnaire to the parents of the students, asking them about their opinion.
What kind(s) of bias is this survey method particularly prone to? How might they be addressed?
Reducing Bias in Sampling
The best technique for reducing bias in sampling is randomization . All of the sampling techniques we already learned (simple random sampling, cluster sampling, stratified sampling, etc.) use randomization, so choose one of those to use, depending on the population.