Population vs. Sample
One of the most important parts of statistics to understand is the difference between a population and a sample. A population is any complete group with one characteristic in common. A sample is a subset of the population that is selected to represent the population.
We will consider an example of a population and a sample with voters in the United States. The population is all registered voters in the United States. The sample is all registered voters that reside in the state of New York. It is apparent in this example that the sample is a subset of the population.
There are a variety of methods used for sampling a population. The two main kinds of sampling methods are probability sampling and non-probability sampling. Probability sampling includes simple random, stratified, cluster, and systematic sampling. Non-probability sampling includes convenience and quota sampling.
The main advantage of using probability sampling is it provides a more representative sample than non-probability sampling. The main advantage of using non-probability sampling is it is easier to obtain the sample compared to probability sampling.