Final answer:
A random sample is more desirable in experimental studies because it minimizes selection bias, helps create comparable groups, and ensures that the data are likely to be normally distributed, all of which contribute to the reliability and generalizability of study results.
Step-by-step explanation:
Importance of Random Sampling in Experimental Studies
Why is a random sample more desirable than other methods of sampling when designing an experimental study? Random sampling is highly desirable because it ensures that every potential subject has an equal chance of being chosen for the study. This equality is crucial for a few reasons. Firstly, it reduces the potential for selection bias, thereby increasing the likelihood that the sample will be representative of the wider population. Secondly, random sampling facilitates the creation of comparable groups within an experimental study, which is essential for isolating the effect of the variable being tested. Thirdly, with sufficient sample size, random sampling helps to ensure that data are more likely to be normally distributed, which is important for the application of many statistical tests. Finally, random sampling can help to ensure variability in sample selection, which is critical for obtaining reliable estimates and for the generalizability of the study's findings.
It's worth noting that other options, such as wider confidence intervals, homogenous group variances, and avoidance of maturation effects, are not primary reasons for preferring random sampling. Although random sampling can indirectly help in achieving homogeneous variances and mitigating maturation effects, these are not its main advantages over other sampling methods.
Convenience samples, like selecting students from an introductory psychology course, can lead to skewed data that do not accurately represent the target population. Hence, despite the practical challenges, random sampling is preferred in experimental design for its beneficial impacts on data quality and study integrity.