Correct Method of Calculating Minimum Sample Size in Quantitative Research: Statistical Power Analysis vs. Slovin's Formula
Suppose a lot of lanzones have been placed in a large tray. If you want to know if they are sweet or not, do you need to count all the lanzones (population)? Not really, right? You just need to taste a sample. The total count of the lanzones (population) is not needed. It's the same in quantitative research. If you want to test whether there is a relationship between X and Y, or if there is a significant difference between the means of groups A and B, or if there is a significant effect of X on Y, you don't need the population size. As long as the research uses statistical tests like T-test, ANOVA, Chi-square test, Pearson correlation, Regression, SEM, among others, the population size is not a requirement. It is incorrect to use Slovin's formula to calculate the sample size when the research employs these statistical models. Refer to the article titled " On the Misuse of Slovin's Formula" The correct way to calculate the minimum sample size for your study i...