Systematic sampling, stratified sampling, and cluster sampling are other types of sampling approaches that may be used instead of simple random sampling.

Researchers choose simple random sampling to make generalizations about a population. Major advantages include its simplicity and lack of bias.

Although simple random sampling is the standard sampling procedure in Monte Carlo simulation, such practice is questioned in this paper. In any Monte Carlo application, sampled distributions are ...

In stratified random sampling, one splits the population into non-overlapping groups (e.g., under 30 years of age, 30 years and over) and then uses systematic or simple random sampling to select ...

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 ...