<P> Sample size determination is the act of choosing the number of observations or replicates to include in a statistical sample . The sample size is an important feature of any empirical study in which the goal is to make inferences about a population from a sample . In practice, the sample size used in a study is determined based on the expense of data collection, and the need to have sufficient statistical power . In complicated studies there may be several different sample sizes involved in the study: for example, in a stratified survey there would be different sample sizes for each stratum . In a census, data are collected on the entire population, hence the sample size is equal to the population size . In experimental design, where a study may be divided into different treatment groups, this may be different sample sizes for each group . </P> <P> Sample sizes may be chosen in several different ways: </P> <Ul> <Li> experience--A choice of small sample sizes, though sometimes necessary, can result in wide confidence intervals or risks of errors in statistical hypothesis testing . </Li> <Li> using a target variance for an estimate to be derived from the sample eventually obtained, i.e. if a high precision is required (narrow confidence interval) this translates to a low target variance of the estimator . </Li> <Li> using a target for the power of a statistical test to be applied once the sample is collected . </Li> <Li> using a confidence level, i.e. the larger the required confidence level, the larger the sample size (given a constant precision requirement). </Li> </Ul> <Li> experience--A choice of small sample sizes, though sometimes necessary, can result in wide confidence intervals or risks of errors in statistical hypothesis testing . </Li>

What is the criteria for selecting a sufficient sample in a given research study
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