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Sampling methods review

What are sampling methods?

In a statistical study, sampling methods refer to how we select members from the population to be in the study.
If a sample isn't randomly selected, it will probably be biased in some way and the data may not be representative of the population.
There are many ways to select a sample—some good and some bad.

Bad ways to sample

Convenience sample: The researcher chooses a sample that is readily available in some non-random way.
Example—A researcher polls people as they walk by on the street.
Why it's probably biased: The location and time of day and other factors may produce a biased sample of people.
Voluntary response sample: The researcher puts out a request for members of a population to join the sample, and people decide whether or not to be in the sample.
Example—A TV show host asks his viewers to visit his website and respond to an online poll.
Why it's probably biased: People who take the time to respond tend to have similarly strong opinions compared to the rest of the population.
Practice problem 1
  • Current
A restaurant leaves comment cards on all of its tables and encourages customers to participate in a brief survey to learn about their overall experience.
What type of sampling is this?
Choose 1 answer:

Good ways to sample

Simple random sample: Every member and set of members has an equal chance of being included in the sample. Technology, random number generators, or some other sort of chance process is needed to get a simple random sample.
Example—A teachers puts students' names in a hat and chooses without looking to get a sample of students.
Why it's good: Random samples are usually fairly representative since they don't favor certain members.
Stratified random sample: The population is first split into groups. The overall sample consists of some members from every group. The members from each group are chosen randomly.
Example—A student council surveys 100 students by getting random samples of 25 freshmen, 25 sophomores, 25 juniors, and 25 seniors.
Why it's good: A stratified sample guarantees that members from each group will be represented in the sample, so this sampling method is good when we want some members from every group.
Cluster random sample: The population is first split into groups. The overall sample consists of every member from some of the groups. The groups are selected at random.
Example—An airline company wants to survey its customers one day, so they randomly select 5 flights that day and survey every passenger on those flights.
Why it's good: A cluster sample gets every member from some of the groups, so it's good when each group reflects the population as a whole.
Systematic random sample: Members of the population are put in some order. A starting point is selected at random, and every n, start superscript, start text, t, h, end text, end superscript member is selected to be in the sample.
Example—A principal takes an alphabetized list of student names and picks a random starting point. Every 20, start superscript, start text, t, h, end text, end superscript student is selected to take a survey.
practice problem 1
  • Current
Each student at a school has a student identification number. Counselors have a computer generate 50 random identification numbers and those students are asked to take a survey.
What type of sampling is this?
Choose 1 answer:

Want to join the conversation?

  • marcimus pink style avatar for user angel
    hey, i was wondering, what type of sampling method does this sentence use? "a biologist surveys all students from each of 15 randomly selected classes."
    (0 votes)
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  • leafers seed style avatar for user nguyentram9613
    I have to design a study and I devide population into 3 age groups. I randomly ask people to answer the survey but only one of three groups are my target and I only take the data of the targeted group. So which sampling method is this case belong to?
    (3 votes)
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  • blobby green style avatar for user Ishaq Khan
    Hi, I am a little confused on the difference between a cluster sample and a stratified random sample. Thanks!
    (3 votes)
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    • eggleston orange style avatar for user jennifer carnell
      Hi Ishaq,
      Cluster samples put the population into groups, and then selects the groups at random and asks EVERYONE in the selected groups.
      A stratified random sample puts the population into groups (eg categories, like freshman, sophomore, junior, senior) and then only a few (people for example) are selected from each sample.
      An example to clarify
      Mia has a population of 50 pupils in her class. She wants to know whether most people like homework or not.
      1. Cluster sampling- she puts 50 into random groups of 5 so we get 10 groups then randomly selects 5 of them and interviews everyone in those groups --> 25 people are asked
      2. Stratified sampling- she puts 50 into categories: high achieving smart kids, decently achieving kids, mediumly achieving kids, lower poorer achieving kids and clueless class-skippers. She then asks 5 of each group at random and sends up asking 25.

      In this case stratified sampling would be a good method to use in my point of view because it is representative of both studious pupils and poorer achieving ones. However, cluster sampling would also be good seeing that it is very random and could also be representative, but it may be more biased to one category of students (eg the smarter ones) than another.

      Hopefully this helped!
      (3 votes)
  • blobby green style avatar for user jill.bowman
    What kind of sampling would this be? "You need a sample of 50 students so you select the first 10 students available for surveying in each of 5 math classes." I am thinking either stratified random sampling or quota (which you don't mention here). Thanks!
    (1 vote)
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  • piceratops tree style avatar for user Jarod Peachey
    Can someone help me?
    Dish network sends a survey with their bill this month. They ask customers to return the survey with their payment. What type of sampling method is this?

    I couldn't match this with any from the article, because it's not random.
    (2 votes)
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  • blobby green style avatar for user Michael Megalakakis
    I am looking for a video in terms of calculating the appropriate sample size for an experiment. Do you have a relevant video on this topic?
    (5 votes)
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  • primosaur ultimate style avatar for user Rithin
    Whats it called when u ask everyone?
    (2 votes)
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  • blobby green style avatar for user Carina Zeeck
    hey, can I make use of convenience sampling and block design at the same time? So, I would randomly ask 150 students from one university to participate and then put half the males in the experimental group and half in the control group (same with the females)?
    (2 votes)
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  • leaf orange style avatar for user Bee Cea
    An average of many different studies of handedness indicate that in a random sample of ​adults,14 percent of men are​ left-handed and 8 percent of women are​ left-handed. (Assume the rest are​ right-handed.) Suppose you have a sample of 350 women and 300 ​men, in which the numbers of​ left-handed and​ right-handed people reflect the average percentages. Make a​ two-way table that shows the distribution you would find.
    (2 votes)
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  • blobby green style avatar for user Paige Desmonie
    The data I'm using is coming from a group of student's "how many times they washed their hands"
    3,7,10,10,10,5,2,35,12,7
    (2 votes)
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