The Sample Size Determination Strategy in the Simple Random Sampling Design
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his paper presents an overview for some strategies concerning the sample size determination including simple random sampling technique in the applied field of science. For this purpose, we introduce details of most commonly used formula for estimating the sample size in the case of dichotomous and continuous outcomes with presenting several effective criteria are affect the size determination. These factors are sampling error or (level of precision), confidence interval CI, and degree of variability (heterogeneity) between unites, proportion of event occurrence (p), population size, and study design. In general level of precision is pointed as ±10% for governmental politics voting survey, ±5% for marketing study, and ±1% for health and industrial purpose survey. This measure is affected by the sample size and can be denoted by SEM if descriptively computed and inferentially can be calculated by (t- test) statistics. In the case of dichotomous outcomes, the proportion of success (p) needs to be stated carefully, because the sample size directly affected by any increasing or decreasing changes volume. Beside these criteria presenting an outline of eight generally used techniques precisely to defined the sample size. We conclude that one technique for determining the sample size is not appropriate for solving all problems. A Specific research problem are needs some specific sample size techniques since initially they based on three different measurements of data (ordinal, nominal or ratio).
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