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.

PSYC20007_2025_SM2 Random Sampling

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

View Explanation

Log in for full answers

Similar Questions

Question at position 20 BEDCA

Which of the following must be necessary to generalize the finding of an observational study to its population of interest?

Which of the following scenarios exemplifies the concept of random sampling?

Question Set H Prompt: Random sampling is a more important consideration than random assignment if the research question is whether faculty tend to drive older cars than students drive on your campus.

The purpose of random sampling is to ensure

Which procedure helps to ensure that the participants in a survey are representative of a larger population?

For results from a study sample to be truly generalizable to a broader population, the study must use

More Practical Tools for International Students

Exam Browser Assistant

Stylized Writing Assistant

Plagiarism Checker Assistant

Citation Assistant

In-Class Translation Assistant

Class Notes Assistant

Quiz Search Assistant

Past Exam Questions by School

Smart Practice Assistant

Adaptive Practice

Making Your Study Simpler