What You Will Learn
- Why sampling methods matter
- Simple random sampling
- Systematic sampling
- Stratified sampling
- Cluster sampling
- Convenience sampling
- How to identify a sampling method from a scenario
Why Does the Sampling Method Matter?
In the previous lesson, we learned that a sample is a subset of a population. But selecting a sample is not simply about choosing some observations.
The way observations are selected can influence whether the sample provides useful information about the population.
Important idea
A large sample is not automatically a good sample. Selection method matters because a poorly selected sample can systematically miss important parts of the population.
Five Sampling Methods
Simple Random Sampling
Every member has a known and equal chance of being selected.
Systematic Sampling
Select observations using a fixed interval after a starting point.
Stratified Sampling
Divide the population into groups and sample from each group.
Cluster Sampling
Divide the population into clusters and select entire clusters.
Convenience Sampling
Select observations because they are easy to access.
1. Simple Random Sampling
In simple random sampling, each member of the population has an equal chance of being selected.
For example, suppose a company has 10,000 employees and wants to select 500 employees for a survey. The company could assign every employee an ID and use a random process to select 500 IDs.
Example
The highlighted IDs represent randomly selected members.
Key idea:
Random selection is used rather than choosing observations based on convenience or preference.
2. Systematic Sampling
In systematic sampling, observations are selected using a fixed interval.
For example, a researcher may select every 10th customer from a list after choosing an appropriate starting point.
Example: Every 5th customer
Here the highlighted observations follow a regular interval.
3. Stratified Sampling
In stratified sampling, the population is divided into meaningful groups called strata. A sample is then taken from each stratum.
This method can be useful when the researcher wants important subgroups of the population to be represented in the sample.
Example: University students
Year 1
Select students
Year 2
Select students
Year 3
Select students
Each year group forms a stratum, and students are sampled from each group.
4. Cluster Sampling
In cluster sampling, the population is divided into groups called clusters. Instead of selecting individual observations from every cluster, the researcher selects some clusters and studies the observations within those selected clusters.
Example: Schools
Suppose a state has 1,000 schools. Researchers randomly select 50 schools and survey students within those selected schools.
The highlighted schools represent selected clusters.
Stratified vs Cluster Sampling
These two methods are often confused because both involve dividing a population into groups. The key difference is what happens after the groups are created.
5. Convenience Sampling
Convenience sampling selects observations because they are easy to access.
For example, a researcher standing outside a shopping mall may ask the first 100 people who agree to participate.
Why be careful?
People who are easiest to reach may differ from people who are difficult to reach. Therefore, convenience sampling can introduce selection bias and may not represent the full population.
Quick Comparison
| Method | How Selection Works | Example |
|---|---|---|
| Simple Random | Randomly select individual members | Randomly select 500 employees |
| Systematic | Select every kth observation | Every 10th customer |
| Stratified | Sample from each group | Students from each year |
| Cluster | Select groups or clusters | Select schools |
| Convenience | Select easily accessible observations | First available participants |
Interactive Practice
Identify the Sampling Method
CHECK YOUR UNDERSTANDING
A company uses a random number generator to select 200 employees from a list of 10,000 employees. Which method is being used?
CHECK YOUR UNDERSTANDING
A researcher selects every 20th customer from a customer list after choosing a starting point. Which method is this?
CHECK YOUR UNDERSTANDING
A university divides students into first-year, second-year, third-year, and fourth-year groups, then samples students from every group. Which method is this?
CHECK YOUR UNDERSTANDING
A researcher randomly selects 10 schools and surveys students within those selected schools. Which method best describes this design?
CHECK YOUR UNDERSTANDING
A researcher surveys people who happen to be standing near the researcher's office because they are easy to reach. Which method is this?
CHECK YOUR UNDERSTANDING
Which sampling method specifically divides a population into groups and then samples from each group?
Fill in the Blanks
Selecting every 10th observation from a list is an example of ______ sampling.
Dividing a population into groups and sampling from every group is called ______ sampling.
Selecting observations because they are easy to access is called ______ sampling.
Selecting some groups and studying observations within those groups is called ______ sampling.
Data Analytics Scenario
Choose the Right Method
An online education platform has students from five different course categories. The analytics team wants students from every category represented in the sample, so they divide students into five groups and randomly select students from each group.
CHECK YOUR UNDERSTANDING
Which sampling method is most directly described?
Key Takeaways
Simple random sampling selects individual observations randomly.
Systematic sampling uses a fixed selection interval.
Stratified sampling samples from each defined group or stratum.
Cluster sampling selects groups or clusters.
Convenience sampling selects observations because they are easy to access.
The sampling method can affect how well a sample represents the population.