Sample (statistics)

Sample (statistics)

In statistics, a sample is a set of data collected and/or selected from a statistical population by a defined procedure. The elements of a sample are known as sample points, sampling units or observations.

Overview

An illustration of a simple random sample

A sample is usually selected for study because it is impractical to study the entire population. The sample should be representative of the general population. This is achieved by methods of sampling.

Types of Sampling

There are various sampling methods. The nature of the population being studied may dictate the methods used for sampling. The main types of sampling methods are:

• Simple random sampling: This is the simplest form of sampling. Every member of the population has an equal chance of being selected.
• Stratified sampling: The population is divided into subgroups (strata) and random samples are taken of each stratum.
• Cluster sampling: The population is divided into groups (clusters). A number of clusters are randomly selected and all members of the selected clusters are included in the sample.
• Systematic sampling: Where members of the population are put into a list and then every nth member is selected to be a part of the sample.

Sample Size

The size of the sample is an important issue in statistical data collection. The larger the sample size, the more reliable the results; however, larger sample sizes are often more costly and may be unnecessary for some studies.

Sampling Error

Sampling error refers to the difference between a sample statistic used to estimate a population parameter and the actual but unknown value of the parameter.

See Also

• Data collection
• Statistical population
• Survey methodology