Short note + 30 objective questions with answers (MCQs) on (d) Sampling. in Research Methodology

 

Sampling

Meaning: Sampling is the process of selecting a small group (sample) from a larger population to study and generalize results for the whole population.

Characteristics: Representativeness, adequacy, accuracy, feasibility, and reliability.

Types:

• Probability Sampling: Simple random, stratified, cluster, systematic.
• Non-Probability Sampling: Convenience, quota, purposive, snowball.

Importance: Saves time and cost, makes research feasible, allows generalization, increases accuracy with proper design.

Steps in Sampling: Define population → Choose sampling frame → Decide sample size → Select method → Collect data.

30 Objective Questions with Answers

1. What is sampling?

Selecting a subset from a population for study.

2. The larger group from which a sample is drawn is?

Population.

3. Main objective of sampling?

To generalize results to the population.

4. Sampling saves?

Time and cost.

5. Simple random sampling is a type of?

Probability sampling.

6. Convenience sampling is a type of?

Non-probability sampling.

7. Stratified sampling is used when?

Population has distinct subgroups.

8. Cluster sampling selects?

Groups/clusters instead of individuals.

9. Systematic sampling selects?

Every kth element from a list.

10. Snowball sampling is useful for?

Hidden or hard-to-reach populations.

11. Purposive sampling selects?

Respondents based on researcher’s judgment.

12. A sample should be?

Representative of the population.

13. In sampling, a frame means?

List of population elements.

14. Larger sample size increases?

Accuracy and reliability.

15. Quota sampling belongs to?

Non-probability sampling.

16. Random number tables are used in?

Simple random sampling.

17. Sampling error arises from?

Studying a sample instead of whole population.

18. Census means?

Study of entire population.

19. Probability sampling ensures?

Equal chance of selection.

20. Non-probability sampling lacks?

Equal chance of selection.

21. Which sampling method is cheapest?

Convenience sampling.

22. Stratified sampling improves?

Representativeness of subgroups.

23. Cluster sampling is suitable for?

Geographically dispersed populations.

24. Example of purposive sampling?

Selecting experts for a study.

25. A key characteristic of good sampling?

Accuracy and representativeness.

26. Sample size depends on?

Population size and study purpose.

27. Snowball sampling uses?

Referrals from respondents.

28. Which sampling gives statistically valid results?

Probability sampling.

29. Sampling is preferred over census when?

Population is large.

30. Main limitation of non-probability sampling?

Cannot generalize results reliably.