Sampling

Sampling is a method used in statistics to select a subset (sample) from a larger population to make inferences about the whole. The goal is to estimate characteristics of the population based on this smaller group.

Population

The entire group of individuals or items you are interested in studying. It includes all possible members relevant to a particular statistical inquiry. For example, if you are studying the height of all students in a school, the population is all students.

Census

If you collect data from everyone in your population, this will be a census.

Sample

A subset of the population that is selected for analysis. Since studying the entire population is often impractical, a sample is used to make inferences about the population. For example, a sample could be 50 randomly selected students from the school.

Random Sampling

There are a number of ways to select the sample. With random sampling, each member of the population has an equal chance of being selected. You can use names out of a hat or number each member of your population and use a random-number generator such as a calculator.

Sampling

If you collect data from your sample, this will be sampling.

Accuracy of sampling

The accuracy of the sample depends on the sample size, denoted as \(n\). Larger sample sizes generally lead to more reliable estimates of the population characteristics.

Sampling is essential for conducting surveys, experiments, and statistical analyses when it's impractical to study an entire population.