Lesson 10
Sampling and sample vs. population
Big question
What is the difference between the data we have and the group we care about?
Lesson progress
Complete checkpoints as you learn
Learning objectives
- Explain sampling and sample vs. population in plain language.
- Use population correctly in an interpretation.
- Connect the lesson idea to a formula, graph, Python result, or real example.
Simple explanation
The population is the full group we want to understand. A sample is the part of that group we actually observe. Econometrics often uses a sample to learn about a larger population.
Key terms
- Population
- The full group of people, firms, regions, or periods we care about.
- Sample
- The observed subset used for analysis.
- Sampling error
- The gap that can occur because a sample is only part of the population.
- Representative sample
- A sample that reflects the population reasonably well.
Sample mean estimates population mean
Example
A survey of 1,000 workers can be used to learn about wages for millions of workers, but the sample must be chosen carefully.
Checkpoint activity
Pause and explain this lesson's main idea in your own words before moving forward.
Try it yourself
Write one plain-English sentence explaining the main idea from this lesson.
Common mistakes
Check these before you move on.
A regression coefficient describes a pattern unless the assumptions or research design support a causal interpretation.
Quick quiz
What is the population?
Key takeaway
Good sampling is the bridge between a dataset and a broader economic claim.