A simple random sample is used to represent the entire data population. A stratified random sample divides the population into smaller groups based on shared characteristics.

Researchers use the simple random sample methodology to choose a subset of individuals from a larger population. While easier to implement than other methods, it can be costly and time-consuming.

This example illustrates how you can use PROC SURVEYMEANS to estimate population means and proportions from sample survey data. The study population is a junior high school with a total of 4,000 ...

As an estimator of the population mean, the sample mean based only on the distinct units possesses a remarkable invariance property. Under three forms of simple random sampling, viz. simple random ...

The example in the section "Stratified Sampling" assumes that the sample of students was selected using a stratified simple random sampling design. This example shows analysis based on a more complex ...

We present a new class of spatial sampling designs, simple latin square sampling + 1. Our approach is quadrat-based in that the study region is partitioned into nonoverlapping quadrats or sampling ...

A statistically designed random sampling scheme, based on as few as 100 people, would give a very high probability of detecting if there are any COVID-19 cases and highlight at-risk hotspots.