Sampling Bias: This occurs when certain individuals or groups are more likely to be included in the sample than others. For example, if a study only includes individuals from urban areas, it may not represent rural populations. Small Sample Size: A sample that is too small may not capture the variability within the population, leading to skewed results. Non-Random Sampling: If the sample is not randomly selected, certain traits may be overrepresented or underrepresented. Exclusion of Key Variables: Failing to account for variables such as age, gender, or genetics can result in a non-representative sample.
