CALCULATING THE OPTIMAL SAMPLE SIZE IN DIFFERENT SITUATIONS

Abstract

The belief is wide spread that studies are unethical if their sample size is not large enough to ensure adequate power .An important step when designing an empirical study is to justify the optimum sample size that will be required. Inappropriate, inadequate, or excessive sample sizes continue to influence the quality and accuracy of research. In order to generalize from a random sample and avoid sampling errors or biases, a random sample needs to be of adequate size .The aim of a sample size justification is to explain how the collected data is expected to provide valuable information given the inferential goals of the researcher. Two distinct investigations conducted on a same sample with the same methodology and achieving equivalent results are different only in terms of sample size .This manuscript describes the procedures for determining sample size using different formulas, a table is provided that can be used to select the sample size for a research problem based on three alpha levels (1%, 5% and10% )and a set of error rate. There are a number of practical issues in selecting the values for the parameters required in the sample size calculation formula. This study presents a summary of how to calculate the survey sample size in social research, information system research, industry, agriculture, and medical studies, to name just a few .In this context, sample size formulae given by different authors have also been discussed in the present article