What does sampling bias refer to in research?

Sampling bias refers to a situation where the sample selected for a study does not accurately reflect the characteristics of the larger population from which it is drawn. This can result in skewed results that do not truly represent the population, leading to flawed conclusions or generalizations. When sampling bias occurs, certain groups may be overrepresented or underrepresented, which can significantly affect the validity of the research findings.

The other options do not accurately characterize sampling bias. For instance, focusing on a larger sample size does not inherently indicate any biases; rather, it may enhance the representativeness if done correctly. Additionally, when the sample is representative of the population, there is no sampling bias present, as the findings would likely reflect those of the larger group accurately. Finally, sampling too quickly could potentially lead to mistakes or imprecision, but it does not specifically describe the fundamental issue of having a biased sample.

Thus, the correct understanding of sampling bias as being associated with non-representative samples clearly establishes why this choice is accurate.