"Sampling error" refers to:
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A. B. C. D.C
Sampling error is the difference between the population's actual parameter and the parameter estimate that results from analysis of the sample.
Sampling error refers to the discrepancy or difference that exists between a sample statistic and the corresponding population parameter. In other words, it is the variation that occurs due to the random selection of a sample from a larger population. The correct answer to the question is C: the difference between a sample statistic and the corresponding population parameter.
Let's break down each answer choice to understand why option C is the correct explanation for sampling error:
A. An incorrect selection of a sampling method: This answer choice is not accurate because sampling error is not related to the selection of a sampling method. Sampling error can occur regardless of whether the sampling method is correct or incorrect. It primarily arises from the random nature of sampling.
B. The standard error of the normal deviates of a sample drawn from a population: While the standard error is a measure of the precision or variability of the sample mean, it is not a direct definition of sampling error. Sampling error encompasses more than just the standard error. It includes the inherent differences between the sample and the population being studied.
C. The difference between a sample statistic and the corresponding population parameter: This option provides the correct definition of sampling error. It highlights that sampling error arises from the inherent variation between a sample and the population it represents. The sample statistic is an estimate or measurement derived from the sample, while the population parameter is the true value of the characteristic being measured in the entire population. Sampling error accounts for the discrepancy between these two values.
D. An incorrect usage of a sampling method: Similar to option A, this answer choice incorrectly suggests that sampling error is related to the correct usage of a sampling method. Sampling error can occur even when the sampling method is correctly implemented. It is primarily a result of random sampling variations and not the misuse of a sampling method.
In summary, sampling error refers to the difference between a sample statistic and the corresponding population parameter. It represents the variation that arises due to the random selection of a sample from a larger population and is independent of the selection or usage of a sampling method.