Recall that there are four ways to collect data: through a census, sample survey, experiment, or observational study.
When we use a sample survey, we select members from a population to be in a study. The method we use to select these members is known as the sampling method.
Here are the various sampling methods we might use:
Simple random sample
Definition: Every member of a population has an equal chance of being selected to be in the sample. Randomly select members through the use of a random number generator or some means of random selection.
Example: We put the names of every student in a class into a hat and randomly draw out names to get a sample of students.
Benefit of this method: Simple random samples are usually representative of the population we’re interested in since every member has an equal chance of being included in the sample.
Stratified random sample
Definition: Split a population into groups. Randomly select some members from each group to be in the sample.
Example: Split up all students in a school according to their grade – freshman, sophomores, juniors, and seniors. Ask 50 students from each grade to complete a survey about the school lunches.
Benefit of this method: Stratified random samples ensure that members from each group in the population are included in the survey.
Cluster random sample
Definition: Split a population into groups. Randomly select some of the groups and include all members from those groups in the sample.
Example: A company that gives whale watching tours wants to survey its customers. Out of ten tours they give one day, they randomly select four tours and ask every customer about their experience.
Benefit of this method: Cluster random samples get every member from some of the groups, which is useful when each group is reflective of the population as a whole.
Systematic random sample
Definition: Put every member of a population into some order. Choosing a random starting point and select every nth member to be in the sample.
Example: A teacher puts students in alphabetical order according to their last name, randomly chooses a starting point, and picks every 5th student to be in the sample.
Benefit of this method: Systematic random samples are usually representative of the population we’re interested in since every member has an equal chance of being included in the sample.
Definition: Choose members of a population that are readily available to be included in the sample.
Example: A researcher stands in front of a library and polls people that happen to walk by.
Drawback of this method: Location and time of day may produce a biased sample of people.
Voluntary response sample
Definition: A researcher puts out a request for volunteers to be included in a study and members of a population voluntarily decide to be included in the sample or not.
Example: A radio host asks listeners to go online and take a survey on his website.
Drawback of this method: People who voluntarily respond will likely have stronger opinions (positive or negative) than the rest of the population, which makes them an unrepresentative sample.