Which of these statements best reflects a good motivation for random sampling necessary?

Question

BlackTom AI · Accepted Answer

When considering why random sampling is used in research, it's helpful to evaluate what each statement implies about the role of randomness in inference.
Option 1: 'If we sample randomly, we are more likely to find robust experimental effects.' While random sampling helps ensure representativeness, it does not guarantee that effects will be robust or larger; robustness depends on the true underlying relationships and experimental design, not just random sampling alone. This statement overstates the impact of random sampling on effect size.
Option 2: 'If we sample randomly, we are more likely to find extreme values.' Random sampling as a concept does not systematically increase the odds of observing extreme values; extreme values can occur by chance in any sample, and random sampling aims to reduce bias, not to bias toward extremes. This makes the claim misleading about what randomness accomplishes.
Option 3: 'If we sample randomly, our results are less likely to be biased by unobserved variables.' This captures a core motivation for random sampling: by giving each unit in the population an equal chance of selection, the sample becomes more representative of the population, thereby reducing bias from unobserved heterogeneity and improving generalizability. It directly links randomness to minimizing selection bias and confounding from unseen factors.
Option 4: 'If we sample randomly, our results will not be contingent on random fluctuations.' This is incorrect because all samples are subject to sampling variability; randomness does not eliminate fluctuations, it is the very source of variability. Statistical methods quantify and account for this variability, but randomness cannot remove it entirely.
In summary, Option 3 precisely reflects the key motivation: random sampling reduces bias from unobserved variables by enhancing representativeness, whereas the other statements misstate the effects or implications of random sampling and its influence on bias, extremes, or fluctuations.

Which of these statements best reflects a good motivation for random sampling necessary?Single choice

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