Certified Internal Auditor (CIA) Practice Test

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Which statement about sampling is true?

  1. A larger sample is always more representative than a smaller sample.

  2. The absolute size of the sample impacts the precision of its results more than its size relative to the population.

  3. A simple random sample always produces the most representative sample for a given sample size.

  4. The limitations of an incomplete sample frame can be overcome by careful sampling techniques.

The correct answer is: The absolute size of the sample impacts the precision of its results more than its size relative to the population.

The correct statement regarding sampling is that the absolute size of the sample impacts the precision of its results more than its size relative to the population. This means that a larger sample size generally results in more reliable and precise estimates of population parameters, regardless of the population size. The principle behind this is that as the sample size increases, the margin of error decreases, which enhances the accuracy of the results obtained from that sample. This concept is rooted in statistical theory, where larger samples tend to provide a more accurate reflection of the population characteristics, thus improving the reliability of statistical inferences drawn from the sample. While the size of the sample relative to the population is important in terms of ensuring appropriate representation, the absolute size is a critical factor in achieving the desired precision in the results. For instance, a small population might require a smaller absolute sample size, but larger samples generally reduce variability and are less susceptible to sampling error, leading to a greater degree of confidence in the results. The other statements do not accurately represent key principles of sampling. For instance, while a larger sample can often be more representative, it is not always guaranteed to be so without considering other factors such as sampling method and design. A simple random sample does not always yield the most representative sample as