Which of the following is the primary reason why bias occurs in sampling?

Bias in sampling primarily arises when the sampling method fails to incorporate randomization, leading to an unrepresentative sample. If certain individuals or groups have a higher likelihood of being selected than others, this can skew the results and create bias. For example, if a survey is conducted only in one region of a country, the data will be biased toward the characteristics of that region and may not accurately reflect the views of the entire population. Random sampling techniques are designed to minimize bias by giving every member of the population an equal chance of being selected. Why Other Options Are Incorrect: • A: A large sample size alone does not cause bias; it can help reduce the impact of random errors. • C: Collecting data from an inappropriate population may lead to misinterpretation, but it does not necessarily result from biased sampling methods. • D: While incorrect analysis can lead to errors, it is not a direct cause of bias in the sample selection. • E: Missing data can affect analysis but does not necessarily introduce bias in sample selection.