Statistical Approach: Science and Application for Determining Optimal Sample Size in empirical study

Abstract

To ensure optimal sample size selection, researchers can use a variety of formulae and procedures created by statisticians to find a suitable sample size. The objects selected have, on average, the same characteristics as the population units if a sufficiently large sample of the population is chosen at random. This is referred to as the statistical regularity principle. According to the statistical regularity principle, larger sample sizes generally produce more accurate and dependable results, assuming that all other variables remain constant.

An ideal sample minimizes the cost for a predefined mean squared error value or lowers the cost for a constant mean squared error. Descriptive cross-sectional secondary sources using readily available statistical tools such as Stata, Survey Monkey, Rao Soft, and G Power provided estimates of the sample size.