What is meant by the term "sampling bias"?

Sampling bias refers to a situation where certain members of a population are systematically excluded from the sample, leading to results that may not accurately reflect the entire population. When this occurs, the data collected may be skewed, causing conclusions drawn from the research to be unreliable.

By systematically excluding certain groups, researchers might miss critical insights and provide a distorted understanding of the phenomenon being studied. For example, if a survey about public health only includes responses from a specific demographic group, it may overlook significant health issues prevalent in other groups, thus creating a biased representation of the population's health.

In contrast, the other options describe scenarios that do not constitute sampling bias. Inclusion of all population members would lead to a complete representation. Random selection ensures that each member has an equal chance of being chosen, which minimizes bias. Convenience sampling relies on selecting participants who are easily accessible, but it does not inherently guarantee systematic exclusion of specific groups, thus not necessarily creating a sampling bias on its own.