3. What do you understand by Sampling? Elaborate various methods of Probability and Non-Probability Sampling.
Answer:
Meaning of Sampling
Sampling is a statistical technique in which only a small part (sample) of the entire population is selected for study, instead of studying the whole population. This sample is carefully chosen so that the information collected from it represents the entire population accurately.
Sampling helps in saving time, cost, and effort, and also makes data collection more practical and feasible.
Methods of Sampling
Sampling methods are broadly classified into two categories:
- Probability Sampling
- Non-Probability Sampling
1. Probability Sampling Methods
In probability sampling, every unit of the population has a known and equal chance of being selected. This method gives more accurate and unbiased results. Methods of Sampling probability
(a) Simple Random Sampling
Each individual of the population has an equal chance of being chosen. Selection is done randomly using methods like lottery or random number tables.
(b) Systematic Sampling
Here, the first unit is selected randomly, and the next units are selected at regular intervals.
Example: Selecting every 10th person from a list.
(c) Stratified Sampling
The population is divided into different groups called strata (such as age, income, gender). From each strata, samples are selected randomly.
This ensures representation of all important groups. Methods of Sampling probability
(d) Cluster Sampling
The population is divided into clusters (groups) like districts, villages, or schools. Some clusters are selected randomly and all or some units from those clusters are studied.
(e) Multistage Sampling
Sampling is done in different stages.
Example: Select districts → then villages → then households. Methods of Sampling probability
2. Non-Probability Sampling Methods
In this method, every unit does NOT have an equal chance of being selected. Selection depends on the judgement or convenience of the researcher. It is less reliable but easier to conduct.
(a) Convenience Sampling
The sample is selected from individuals who are easily available.
Example: Surveying students in a nearby college. Methods of Sampling probability
(b) Judgement or Purposive Sampling
The researcher selects the sample based on their own judgement about who will give the best information.
Example: Selecting expert doctors for a health survey.
(c) Quota Sampling
The population is divided into groups (like male/female), and a fixed number (quota) is selected from each group based on convenience. Methods of Sampling probability
(d) Snowball Sampling
Used when the population is difficult to identify. Existing respondents help in identifying more respondents.
Example: Survey among drug addicts or rare disease patients.
Conclusion
Sampling is an essential tool in statistics that helps in collecting accurate information in a cost-effective and time-efficient manner. Probability sampling is more scientific and unbiased, while non-probability sampling is easier but less reliable. Methods of Sampling probability
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