Sampling and it's Types | Probability and Non probability sampling | What is Population and Sample?

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Sampling
Definition: Sampling is the process of selecting a subset of individuals or units from a larger population to represent the entire population.


Types of Sampling


➡Probability Sampling

1. Simple Random Sampling (SRS)
2. Stratified Random Sampling
3. Cluster Sampling
4. Systematic Random Sampling
5. Multistage Sampling


➡Non-Probability Sampling

1. Convenience Sampling
2. Judgmental Sampling (Purposive Sampling)
3. Quota Sampling
4. Snowball Sampling


Probability Sampling Methods
1. Simple Random Sampling (SRS): Every individual has an equal chance of selection.
2. Stratified Random Sampling: Population divided into subgroups, sampling from each.
3. Cluster Sampling: Sampling groups or clusters, not individuals.
4. Systematic Random Sampling: Selecting individuals at regular intervals.
5. Multistage Sampling: Combining multiple sampling methods.


Non-Probability Sampling Methods
1. Convenience Sampling: Selecting participants based on ease of access.
2. Judgmental Sampling (Purposive Sampling): Selecting participants based on expertise or knowledge.
3. Quota Sampling: Selecting participants to meet specific demographic quotas.
4. Snowball Sampling: Participants recruit future participants from their social networks.
5. Accidental Sampling: Selecting participants encountered by chance.


Key Differences
Probability Sampling
Random selection
Equal chance of selection
Representative of population
Generalizable results


Non-Probability Sampling
Non-random selection
Unequal chance of selection
May not represent population
Limited generalizability


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