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Course: Statistics and probability > Unit 6
Lesson 3: Sampling methodsSampling 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.
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 teacher 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 students by getting random samples of freshmen, sophomores, juniors, and 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 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 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 student is selected to take a survey.
Want to join the conversation?
- Hi, I am a little confused on the difference between a cluster sample and a stratified random sample. Thanks!(4 votes)
- 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!(10 votes)
- 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)
- Why are there so many types of Sampling?and why do we use these samples?(2 votes)
- There are many types of sampling methods because different research questions and study designs require different approaches to ensure representative and unbiased samples. Using appropriate sampling techniques helps researchers generalize their findings to the broader population and reduces the risk of introducing biases that could invalidate study results. Each sampling method has its strengths and weaknesses, and researchers choose the most suitable method based on the specific objectives of their study and the characteristics of the population being studied.(3 votes)
- Whats it called when u ask everyone?(2 votes)
- census, but it is not a sample since you are asking everyone(3 votes)
- Why are there so many types of sampling?(2 votes)
- When taking a stratified random sample, do the strata need to be proportionate to that group's representation in the population?
For example if a school wants to do a stratified random sample of 100 students and it has 1000 students and 200 are freshmen, 400 are sophomores, 300 are juniors and 100 are seniors should the number selected for the study be 20-40-30-10 or should it be 25-25-25-25 for each of the grades?(2 votes) - I really don't know why everything has to just keep on making me so mad right now no(2 votes)
- If I wanted to do a study of who cooks as home with my sample being people who go to the gym what kind of sampling should I use?(2 votes)
- For a study on cooking habits among people who go to the gym, you could use a stratified random sampling method. Stratify the population of gym-goers based on relevant characteristics such as age, gender, or frequency of gym visits, and then randomly select individuals from each stratum to ensure representation across different subgroups.(1 vote)
- 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.(1 vote)- If they send it to every customer, voluntary response because customers choose to be part of the sample. This sample is biased.(2 votes)
- 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?(4 votes)