Introduction
Sampling is the process of selecting a small group (sample) from a large population for research. It helps researchers save time, money, and effort while still getting useful data. Proper sampling methods make the research more reliable and representative.
Types of Sampling Methods
Sampling is mainly divided into two categories: probability sampling and non-probability sampling.
I. Probability Sampling Methods
In this method, every member of the population has a known chance of being selected. It is considered scientific and unbiased.
1. Simple Random Sampling
Every member has an equal chance of being selected. Names can be picked from a hat or using a computer program.
Example: Selecting 50 students randomly from a list of 500.
2. Systematic Sampling
Selecting every nth item from a list after a random start.
Example: Choosing every 10th patient in a hospital register.
3. Stratified Sampling
The population is divided into groups (strata) like age, gender, income, etc. Then a sample is taken from each group.
Example: Selecting students from different classes (Class 6, 7, 8) to ensure all levels are included.
4. Cluster Sampling
Population is divided into clusters (groups), and a few clusters are randomly selected. All members in selected clusters are included in the sample.
Example: Selecting 3 villages randomly from a district and studying all women in those villages.
II. Non-Probability Sampling Methods
In this method, not all members have a chance of being selected. It is often used in social work due to time or cost limits.
1. Convenience Sampling
Samples are taken from people who are easy to reach.
Example: Interviewing students available at the college gate.
2. Purposive Sampling
Samples are selected based on a specific purpose or judgment of the researcher.
Example: Selecting only women leaders from SHGs for interviews.
3. Snowball Sampling
Existing subjects refer new subjects. Often used with hard-to-reach populations.
Example: Interviewing drug users, where one person introduces the next.
4. Quota Sampling
Sample includes specific numbers from different groups.
Example: 40% women and 60% men in a survey.
Importance of Sampling
- Saves time and cost.
- Makes data collection easier.
- Useful when studying a large population.
- Allows better focus and detailed study.
Conclusion
Sampling is an essential part of social work research. Choosing the right sampling method ensures the data is accurate and trustworthy. Whether it is a random sample or a purposive one, the method must match the research goal and available resources.