Learn how simple random sampling works and what advantages it offers over other methods when selecting a research group from a larger population.

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.

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 ...

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 ...

The case for the central limit theorem for the sample mean from finite populations under simple random sample without replacement, the parallel to the simplest case in the standard framework, is not ...

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.