Sampling

(Leavy, 2022)

Sampling:

1. Involves selecting subjects, respondents, participants, or collaborators.

2. Element: The kind of person, group, or nonliving item of interest.

3. Population: Group of elements about which claims are made.

4. Study Population: Elements from which the sample is drawn.

5. Sample: Number of individual cases from which data is generated.

Determining Sample Size:

6. Questions to determine size: Research questions, available resources, research method.

7. Quantitative research favors larger samples.

8. Online calculators help determine ideal sample size.

9. Factors include population size, confidence level, margin of error.

Sample Size in Qualitative and Arts-Based Approaches:

10. Smaller sample sizes in qualitative and arts-based approaches.

11. No strict rules; it depends on the project.

12. Consider factors like breadth, depth, nature of the topic, population characteristics, analysis level, and practical parameters.

13. Value data that contribute to new learning.

Saturation in Qualitative Research:

14. Saturation point: Additional data don't yield new insights.

15. Theoretical saturation: Stop when new participants don't provide new information.

16. Grounded theory uses saturation to guide data collection.

Sampling Procedures:

17. Two categories: Probability sampling and purposeful sampling.

18. Probability sampling in quantitative research for statistical generalization.

19. Types of probability sampling: Simple random, systematic, cluster, stratified.

20. Purposeful sampling in qualitative, ABR, and CBPR for in-depth understanding.

21. Different purposeful sampling strategies, including single significant case, comparison-focused, group characteristics, and more.

22. Snowball Sampling: One case leads to another.

23. Homogeneous Sampling: Cases share a common characteristic.

These points cover key aspects of sampling, sample size determination, and different sampling procedures in research.