Sampling Methods

Sampling Methods

1. Probability Sampling

   • Simple random
     • Is a subset of a population in which each member of the subset has an equal probability of being chosen. Unbiased representation of a group.
       • E.g. Names of 25 employees being chosen out of a hat from a company of 250 employees.
   • Systematic
     • A type of probability sampling method in which sample memebers from a larger population are selected according to a random starting point and a fixed, periodic interval. This interval, called sampling interval, is calculated by dividing the population size by desired sample size.
       • E.g. If you wanted to select a random group of 1,000 people from a population of 50,000 using systematic sampling, all potential participants must be placed in a list and a starting point would be selected. Once the list is formed, every 50th person on the list (starting the count at a selected counting point) would be chosen as a participant, since 50,000/1,000 = 50.
         • For example, if the selected starting point was 20, the 70th person on the list would be chosen followed by the 120th, and so on.
   • Stratified
     • Is a method of sampling that involves the division of a population into smaller groups known as strata. In stratified random sapling, or stratification, the strata are formed based on members' shared attributes or characteristics.
   • Cluster random
     • Researcher divides the population into separate groups, called clusters. Then, a simple random sample of clusters is selected from the population. Researcher conducts their analysis on data from the sampled clusters.
       • E.g. a researcher wants to survey academic performance of highschool students in Spain. He can divide the entire population (population of Spain) into different clusters (cities). Researcher then selects a number of clusters depending on his research through simple or systematic random sampling.
   • The odds are the same for any particular participant being chosen

2. Non-probability Sampling

   • Snowball
     • Snowball sampling is where research participants recruit other participants for a test or study. It is used when potential participants are hard to find. It's called snowball sampling because (in theory) once you have the ball rolling, it picks up more "snow" along the way and becomes larger and larger.
       • For example, if obtaining subjects for a study that wants to observe a rare disease, the researcher may opt to use snowball sampling since it will be difficult to obtain subjects. It is also possible that the patients with the same disease have a support group; being able to observe one to the members as your initial subject will then lead you to more subjects for the study.
   • Convenience
     • Sampling technique where subjects are selected because of their convenient accessibility and proximity to the researcher.
       • One of the most common examples of convenience sampling is using student as volunteers as subjects for the research.

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