Biased Sample

Biased Sample Definition

A biased sample is a selection of individuals from a larger population that does not accurately reflect the characteristics or composition of that parent population, meaning it is not representative. When investigating phenomena within a population, such as voting intentions, a sample must be truly reflective of the whole group to yield acceptable data. If this representation is not properly managed, bias is introduced, causing the collected information to inaccurately represent the population under study.

Implications for Data Collection

The failure to select a representative sample leads directly to biased results. For instance, sampling methods that rely on convenience, such as questioning people in public spaces, systematically exclude certain segments of the population (e.g., those who do not walk, shop, or are engaged in work or study), thereby skewing the findings against those excluded groups.

Mitigating Sampling Bias

To minimise bias and ensure data validity, careful selection procedures are essential. Where true random sampling is unfeasible, researchers must meticulously match all relevant demographic parameters of the population, including age, class, and residence. Furthermore, efforts should be made to maximise response rates, often achieved through personal interviewing, which can help mitigate biases introduced by non-response or literacy levels associated with methods like postal questionnaires.