How can a researcher avoid a biased sample?
A researcher can avoid bias in their sample methods, size, and variation.
There are many factors that can lead to bias and must be avoided. Three examples are given here.
A researcher must avoid bias in their sample methods. This means they must practice the same methods consistently for each sample. They must also be easily replicable to ensure that others can repeat the study, essentially checking the results.
The researcher must have a sufficient sample size. It is bias to selectively use a small data set that does not effectively reflect the broader trend.
The researcher must have enough variation in the sample. For example, consider a researcher surveying college students about the frequency of their exercise. If the researcher asks only men or only science majors, they may have a biased study that cannot be generalised to accurately represent a population.