What is the difference between population and sample?

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The difference between a population and a sample lies in the scope and purpose of the data being studied.

✅ Population:

  • The entire group you want to study or gather information about.

  • It includes all possible individuals, items, or data points that fit your criteria.

  • Populations can be finite (e.g., all students at a school) or infinite (e.g., all possible rolls of a die).

🧠 Example:
If you're studying college students in the U.S., the population is all college students in the country.

✅ Sample:

  • A subset of the population, selected for the purpose of analysis.

  • Used because studying the entire population is often impractical or impossible.

  • A good sample should be representative of the population to ensure accurate conclusions.

🧠 Example:
If you survey 1,000 college students from various states, that group is your sample.

📊 Why It Matters:

  • Researchers use samples to make inferences about the larger population.

  • Proper sampling methods (e.g., random sampling) help reduce bias and increase reliability.

✅ Summary:

A population is the full group you're interested in, while a sample is a smaller group selected from it for study. Samples help you draw conclusions about populations efficiently.

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