SAMPLE SIZE ESTIMATION USING KREJCIE AND MORGAN AND COHEN STATISTICAL POWER ANALYSIS: A COMPARISON

In most situations, researchers do not have access to an entire statistical population of interest partly because it is too expensive and time consuming to cover a large population or due to the difficulty to get the cooperation from the entire population to participate in the study. As a result, researchers normally resort to making important decisions about a population based on a representative sample. Hence, estimating an appropriate sampling size is a very important aspect of a research design to allow the researcher to make inferences from the sample statistics to the statistical population. The power of a sample survey lies in the ability to estimate an appropriate sample size to obtain the necessary data to describe the characteristics of the population. With that as the rationale, this article was written to make comparison between two commonly used approaches in estimating sampling size: Krejcie and Morgan and Cohen Statistical Power Analysis. It also highlights the significance of using Cohen’s formula over Krejcie and Morgan’s for higher accuracy to base decisions on research findings with confidence.