Why is random sampling important in research?

Why is random sampling important in research?

• A. It allows researchers to manipulate variables
• B. It ensures that the sample is representative and reduces bias
• C. It generates large sets of qualitative data
• D. It limits the types of data collected

Answer: (B)

Random sampling is crucial in research because it ensures that every individual in the population has an equal chance of being selected for the sample. This method helps to create a representative sample, which can more accurately reflect the characteristics of the entire population. When a sample is representative, the findings and conclusions drawn from the research can be generalized to the broader population with greater confidence. Furthermore, random sampling reduces selection bias, which can occur when certain members of a population are more likely to be selected than others, potentially skewing results. By minimizing bias, researchers can achieve more valid and reliable outcomes, strengthening the overall credibility of their study. This is particularly important in criminal justice research, where decisions based on results can have far-reaching implications for policy and practice.

Random sampling is crucial in research because it ensures that every individual in the population has an equal chance of being selected for the sample. This method helps to create a representative sample, which can more accurately reflect the characteristics of the entire population. When a sample is representative, the findings and conclusions drawn from the research can be generalized to the broader population with greater confidence.

Furthermore, random sampling reduces selection bias, which can occur when certain members of a population are more likely to be selected than others, potentially skewing results. By minimizing bias, researchers can achieve more valid and reliable outcomes, strengthening the overall credibility of their study. This is particularly important in criminal justice research, where decisions based on results can have far-reaching implications for policy and practice.