In research, there are two types of samples you can draw: a probability sample where every person in the sample has an equal and known probability of being selected, and a non-probability sample where the probability of a person being selected is unknown.

Probability samples are preferable; however, they are rarely available in real life. As a result, non-probability samples are often used in research.

Examples of probability samples are:

• Simple Random Sample—This occurs where every element has a known and equal probability of being selected. A true random sample is rarely used because we rarely have a sample frame that lists every person we could sample.
• Systematic Sample—This occurs when all potential respondents have a known and equal chance of being selected. To create a systematic sample, select every nth person from the list of potential respondents starting from a number y. Y should be chosen at random, and n should allow for you to get through the list exactly once with a complete sample. This will form a simple random sample of respondents if the customer list is not systematically ordered in some way.
• Stratified Sample—This is desirable if the population is to be broken up into different groups based on characteristics of the population. The distinguishing characteristics, called “strata,” are identified and used to segment potential respondents. A simple random sample is drawn within each segment. Once the survey is completed, the strata are then weighted back to the population proportions.

Examples of non-probability samples are:

• Quota Sample—This assures that various subgroups of the population are represented on relevant sample characteristics. For example, a quota sample may be used to make sure you have at least 35 people who have an income more than \$250,000.
• REFERRAL SAMPLE—This is used to locate a population of rare individuals by referral. Locating 100 adult croquet players may be difficult without referrals.
• Convenience Sample—These are based on convenience and may include members of affiliation groups, interest groups, or random intercepts on your website. The objective is to collect as much data as possible, regardless of where they come from.