What does random sampling ensure in a study?

Random sampling is a method used in research to create a sample that accurately represents a larger population. The primary purpose of random sampling is to ensure that every individual in the population has an equal chance of being included in the sample. This approach helps eliminate selection bias, as it provides each member of the population with an opportunity for inclusion regardless of specific characteristics.

When random sampling is effectively implemented, it increases the likelihood that the sample will reflect the diversity of the population, leading to more generalizable findings. This method is crucial for obtaining valid conclusions about the population based on the sample data collected. In contrast, other approaches may lead to skewed results because certain demographics could be overrepresented or underrepresented. This inclusion of each individual in the sampling process helps researchers draw more accurate inferences about population behaviors, attitudes, or characteristics.

While equal representation of demographics, elimination of biases, and random distribution of variables can also be associated with sound research practices, they do not encapsulate the core principle of what random sampling accomplishes. Random sampling directly addresses the probability of selection, making option B the most accurate description.