It is the process of choosing a representative sample from a target population and collecting data from that sample in order to understand something about the population as a whole.
Types of Random Sampling
Simple
selecting a group of subjects (a sample) from a larger group (a population).
meant to be an unbiased representation of a group and a fair way to select a sample from a larger population
each member has an equal chance of getting selected.
Example: selecting 25 employees from a company of 250 employees.
Stratified
came from the word stratum (pl. stratum) which means subgroup.
divides the population into subpopulations
often used in populations with a distinct elements or classifications.
Example: If a farmer may want to milk each cow breed, he could divide his cows into subgroups based on their breed and collect milk.
Multistage
constructed by taking a series of simple random samples
more practical than simple random sampling in cases that require on location analysis like door-to-door surveys.
Other Statistical Terms
Parameter
These refers to numbers that summarize the data for the entire population.
A numerical quantity that tells something about the population
Statistic
These are numbers that summarize data from a sample
Like the parameter, it is a numerical quantity or some measurement that tells something about the sample (or an attribute of a sample).