1.2.2 - Sampling Methods

There are many different ways to select a sample from a population. Some of these methods are probability-based, such as the simple random sampling method, which you'll read about below and in your textbook. Other probability-based methods include cluster sampling methods and stratified sampling methods. You may learn more about these if you take a research methods course or an advanced statistics course in the future. Other sampling methods are not probability-based, such as convenience sampling methods, which you will read about below.

Simple Random Sampling Section

To prevent sampling bias and obtain a representative sample, a sample should be selected using a probability-based sampling design which gives each individual a known chance of being selected. The most common probability-based sampling method is the simple random sampling method.

Using this method, a sample is selected without replacement. This means that once an individual has been selected to be a part of the sample they cannot be selected a second time. If multiple samples are being taken (e.g., when constructing a sampling distribution in Lesson 4), an individual can appear in more than one sample, but only once in each sample.

Simple Random Sampling
A method of obtaining a sample from a population in which every member of the population has an equal chance of being selected

Example: Community Service Attitudes Section

An institutional researcher is conducting a study of World Campus students’ attitudes toward community service. He takes a list of all 12,242 World Campus students and uses a random number generator to select 30 students whom he contacts to complete the survey. This researcher used simple random sampling because participants were selected from the overall population in a way that each individual had an equal chance of being selected.

Example: Languages Section

A student wants to learn more about the languages spoken in her town. She has access to the census forms submitted by all 3,500 households in her town. It would take too long for her to go through all 3,500 forms, so she uses a random number generator to select 100 households. She finds those 100 census forms and records data concerning the languages spoken in those households. This is a simple random sample because the sample of 100 households was selected in a way that each of the 3,500 households had an equal chance of being selected.

Convenience Sampling Section

While probability-based sampling methods are considered better because they can prevent sampling bias, there are times when it is not possible to use one of these methods. For example, a researcher may not have access to the entire population. In cases were probability-based sampling methods are not practical, convenience samples are often used.

Convenience Sampling
A method of obtaining a sample from a population by ease of accessibility; such a sample is not random and may not be representative of the intended population.

Example: Weight Loss Supplements Section

A weight loss company wants to compare how much weight adults lose on their supplement versus a competitor's supplement. To recruit participants, they post an advertisement in a newspaper asking for adults who want to lose weight. This is an example of a volunteer sample which is a convenience sampling method. The researchers are using a sample of individuals who volunteer to participate.

Example: Chocolate Preferences Section

A chocolate company wants to know if customers prefer their dark chocolate with or without peanuts. They set up a table in a grocery store on a Monday morning, offer customers samples of their dark chocolate with and without peanuts, and ask which they prefer. This is an example of a convenience sampling method. The sample is not being selected using any probability-based method and may not be representative of the company's intended population. People who grocery shop may be a special subset of the population.  For example, people who do not work traditional full-time jobs may be more likely to grocery shop at that time. The researchers are using a sample of individuals who happen to be grocery shopping on a Monday morning and who volunteer to eat their chocolate.