What is meant by sampling bias?

Sampling bias refers to a systematic error that occurs when the sample chosen for a study does not accurately represent the larger population from which it is drawn. This misrepresentation can lead to results that are skewed or not reflective of the true characteristics of that population. When sampling bias is present, certain groups within the population may be overrepresented or underrepresented, which can affect the validity of conclusions drawn from the research.

For example, if a survey about consumer preferences only targets a specific demographic, it fails to capture the views of the entire population, thus leading to biased results. Recognizing and addressing sampling bias is crucial for ensuring the reliability and generalizability of research findings, which is why option B is the correct answer.

The other options depict inaccuracies related to the concept of sampling bias. While a representative sample is crucial for accurate research, sampling bias is an error that actually arises from the lack of proper representation. An accurate reflection of population characteristics denotes the opposite of bias, and reducing variability in research is a different issue related to study design rather than sample representation.