Sampling techniques are used to select a subset of data from a larger dataset. The goal is often to make inferences about the entire dataset or to reduce the size of the dataset for analysis. There are a couple of ways to work on Sampling.
Random Sampling
Each member of the population has an equal chance of being selected.
Stratified Sampling
The population is divided into strata, and samples are taken from each stratum.
Systematic Sampling
Every nth member of the population is selected.
Cluster Sampling
The population is divided into clusters, and entire clusters are randomly selected.
Convenience Sampling
Samples are taken from a group that is conveniently accessible.