![]() One method is to suppose that the variable of interest has a random order in the population, so the sample variance of simple random sampling without replacement is used. There are several ways to circumvent this problem. The drawback of this simplicity is that it is not possible to estimate the design variance without bias. Systematic sampling is a commonly used technique due to its simplicity and ease of implementation. We will show here that under this scenario simple random sample can be given a Bayesian justification in survey sampling.Īn unbiased estimator of the variance of simple random sampling using mixed random-systematic sampling Recently it has been argued that the sampling design can be thought of as part of a Bayesian's prior distribution. Although a close relationship between exchangeable prior distributions and simple random sampling has been noted how to formally integrate simple random sampling into the Bayesian paradigm is not clear. ![]() A Bayesian Justification for Random Sampling in Sample Surveyĭirectory of Open Access Journals (Sweden)įull Text Available In the usual Bayesian approach to survey sampling the sampling design, plays a minimal role, at best. ![]()
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