Notes in Statistics Compiled by: Definition of Scientific Research (original) (raw)
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Perhaps the most frequently asked question concerning sampling is, "What size sample do I need?" The answer to this question is influenced by a number of factors, including the purpose of the study, population size, the risk of selecting a "bad" sample, and the allowable sampling error. Interested readers may obtain a more detailed discussion of the purpose of the study and population size in Sampling The Evidence Of Extension Program Impact, PEOD-5 (Israel, 1992).
Sampling Error in Survey Research
2019
In survey research, all deficiencies or weaknesses are caused by sampling or non-sampling issues that engender the discrepancy between sample value and population value. When the sample values deviate from the population value due to sampling, the deviation is termed as sampling error. It is statistically measured in term of standard error that is used to determine confidence interval to quantify the accuracy of the sample estimates. Unlikely the standard error from a sample distribution, estimated standard error can be calculated bases on the standard deviation derived from a random sample. An appropriate size of a sample can be a better estimator than a large size sample if it consists of similar characteristics of a population. Well defined target population, an exhaustive list of sample frame, effective sample design, reasonable sample size, acceptable level of confidence level are common measures to balance the
Statistics review 2: samples and populations
Critical care (London, England), 2002
The previous review in this series introduced the notion of data description and outlined some of the more common summary measures used to describe a dataset. However, a dataset is typically only of interest for the information it provides regarding the population from which it was drawn. The present review focuses on estimation of population values from a sample.
MATHEMATICAL JOURNAL OF INTERDISCIPLINARY SCIENCES, 2014
One of the questions most frequently asked of a statistician is: how big should the sample be? Managers are anxious to obtain an answer to this fundamental question during the planning phase of the survey since it impacts directly on operational considerations such as the number of interviewers required. There is no magical solution and no perfect recipe for determining sample size. It is rather a process of compromise in which the precision requirements of the estimates are weighed against various operational constraints such as available budget, resources and time. In this article we revisit to the estimate of sample size for various project characteristics. Examples for each are supported numerically.