What is a true statement about bias in sampling?

The selected statement about bias in sampling is indeed accurate. Bias in sampling refers to any systematic error that causes a sample to be unrepresentative of the population from which it is drawn. When sampling methods do not adequately capture the characteristics of the entire population, bias is likely to occur. For instance, if certain groups within a population are overrepresented or underrepresented due to the sampling methods, the results may skew, leading to conclusions that do not accurately reflect the views or characteristics of the overall population.

Addressing the other statements helps clarify the importance of understanding bias in sampling. Enhancing the accuracy of results contradicts the very nature of what bias represents, which is a departure from true representation. Claiming that bias always occurs with simple random sampling is incorrect because simple random sampling, when done correctly, is one of the best methods to minimize bias. Finally, the assertion that bias can be entirely eliminated is misleading, as while it can be significantly reduced through careful sampling design, it is nearly impossible to eliminate all forms of bias in practical settings.