Final answer:
A statistical sample differs from a judgmental sample in that it allows for population estimates with measurable reliability using confidence intervals and randomization to reduce bias and improve the accuracy of the results.The correct option is A. No judgment is required because everything is computed according to a formula.
Step-by-step explanation:
An important difference between a statistical sample and a judgmental sample is that with statistical sampling, population estimates with measurable reliability can be made. Statistical sampling methods, such as simple random sampling, stratified sampling, and other probability-based techniques, ensure that each individual in the population has an equal chance of being included in the sample, thereby reducing bias and increasing the reliability of the results.
Statistical samples allow researchers to create confidence intervals, which are ranges within which the true population parameter is expected to lie with a certain level of confidence. A statistical sample is critical in inferential statistics, which is the process of using sample data to make generalizations or inferences about a population. Unlike judgmental samples, where the selection of sampling units involves subjective judgment, statistical samples apply randomization and mathematical rigor to the selection process.
Larger sample sizes, when selected appropriately, yield results that better approximate the actual population parameters, thus reducing sampling variability. This variability refers to the differences that might arise between various samples from the same population. In practice, large enough samples that are well-chosen are considered to provide results that are both accurate and reliable.