Sampling in Research
Sampling in Research
Definition:
Sampling is the process of choosing a representative group from the total population for research purposes.
Important Terms
1. Population: The whole group about which the researcher wants information.
2. Sample: A smaller group selected from the population.
3. Sampling Technique: The method used to select the sample.
Purpose of Sampling
• Saves time
• Saves money
• Easier to conduct research
• Gives quick results
• Useful when population is very large
Types of Sampling
Sampling is divided into two types:
1. Probability Sampling
2. Non-Probability Sampling
A. Probability Sampling
1. Simple Random Sampling
Selection is done randomly, such as by lottery method.
Advantages: Easy, no bias, accurate results.
Disadvantages: Time consuming, difficult in large populations.
2. Systematic Sampling
Every nth person is selected.
Example: Every 5th patient in OPD.
Advantages: Simple and organized.
Disadvantages: May miss important data.
3. Stratified Sampling
Population is divided into groups called strata.
Advantages: Better representation and accuracy.
Disadvantages: Complicated process.
4. Cluster Sampling
Population is divided into clusters.
Advantages: Economical and useful for large areas.
Disadvantages: Less accurate.
B. Non-Probability Sampling
1. Convenience Sampling
Samples are selected because they are easily available.
Advantages: Fast and cheap.
Disadvantages: Biased results.
2. Purposive Sampling
Researcher selects people with specific characteristics.
Advantages: Useful for special studies.
Disadvantages: Personal bias possible.
3. Quota Sampling
