Defining the Different Kinds of Sampling Methods

Defining the Different Kinds of Sampling Methods
Simple Random Sampling
Of all the sampling methodologies, simple random sampling is one of the most commonly used because it is easy to implement and analyze. Moreover, because samples are chosen randomly, it is by using this method, researchers are able to utilize statistical analysis to understand the characteristcs of a given sample.
The traditional way of obtaining a random sample is the lottery method wherein all members of the population are assigned a unique number. These numbers are written on a piece of paper and compiled in a bowl and mixed. A blind folded researcher will then select several numbers (depending on the what the population and research design is). The number/s chosen are then included in the sample. Today, however, there are already various websites that offers random number generators so researchers can get random quickly and with minimum sampling bias.
Systematic Sampling
Systematic random sampling is a favorite among researchers because it is easy to do, and it provides a system in the selection of subject so it typically produces a sample that is highly representative of the population. It also gives an assurance to the population that the sampling is spreadout so there is an even greater chance to be selected as part of the sample.
Before the sampling procedure begins, the researcher has to identify two things: 1) the number of sample he needs for his study, and 2) the interval between the samples. For the purpose of this description, let's pretend that the researcher needs 30 samples, and the interval is 10.
The sampling procedure begins with a researcher randomly picking the first item or subject. He then counts out the interval, starting from the first item. So in the example above, the researcher chose five (5) as the first number, the members of the sample would be 5, 15, 25, 35, 45, 55.... including every 10th item/subject in the population until he gets a total of 30 item/subjects.
Some researchers utilize the modified systematic random sampling procedure. Here, they identify the required sample size and then they divide the total number of the population size with the sample size in order to get a fraction. This sampling fraction is used as the interval.
Stratified Random Sampling
In stratified random sampling, the researcher has to divide the population into different subgroups (the categories of which are dictated by the needs of the study), before the sample is selected. The categories of the groups must not overlap so that each subject in the population can only be included in one category. Some categories that can be used is gender, age, nationality, religion, etc.
Stratified random sampling is used when the res...