In statistics, and survey methodology, sampling is concerned with the selection of a subset of individuals from within a statistical population to estimate characteristics of the whole population.

Two advantages of sampling are that the cost is lower and data collection is faster than measuring the entire population.

For statistical procedures to be valid it is important to use the principles of experimental design in your process of sample selection (randomisation, replication and reduction of experimental error).
 

Each observation measures one or more properties (such as weight, height, yield, grain colour) of the experimental unit. These are independent plot, plants, individuals. or households.

In survey sampling, weights can be applied to the data to adjust for the sample design, particularly if the survey is  stratified.

Results from probability theory and statistical theory are employed to guide practice. In business and medical research, sampling is widely used for gathering information about a population.

The sampling process comprises several stages:
 

• Defining the population of concern (sometimes defined as a target population)

• Specifying a sampling frame, which is a list, or a set of items or events which it is possible to measure.

• Specifying a sampling method for selecting items or events from the frame. In  a field trial this involves sampling from each experimental unit (or plot) independently.

• Determining the sample size

• Implementing the sampling plan

• Analysis and reporting and communicating results