In survey research, what does a non-random sample typically lead to?

In survey research, utilizing a non-random sample generally leads to bias in the survey outcomes. This happens because a non-random sample does not adequately represent the larger population from which it is drawn. When certain groups or perspectives are overrepresented or underrepresented, the results may reflect the views or characteristics of those specific groups rather than the population as a whole. Consequently, the findings can misrepresent trends, behaviors, or opinions, leading to conclusions that may not be generalizable or accurate for the entire population.

This bias can result from various factors, such as the method of selecting participants, the setting where the survey takes place, or the characteristics of those who choose to respond. Unlike a random sample, which aims to eliminate systematic differences between segments of the population, a non-random sample introduces inherent biases, affecting the validity and reliability of the research outcomes.