Comparison of sampling methods with real data

In this study, Simple Random Sampling, Stratified Random Sampling, One-Stage Cluster Sampling and Two-Stage Cluster Sampling, which are used in many studies, were discussed. In this context, the average number of students studying in departments at Ondokuz Mayıs University was estimated according to the methods given above and the variances of the estimators were calculated. It was observed that the variance of the estimator made with Stratified Random Sampling was smaller than the variances of other estimators. Neyman distribution was used to distribute the sample selected by Stratified Random Sampling to the strata. Then, the confidence intervals of the parameters of the estimators were given according to these four different methods. Therefore, the parameter estimated by Stratified Random Sampling was obtained in a narrower area than the confidence intervals found for other methods.