Sampling Meaning and Types

1. Gopal Narayan Singh university
Jamuhar rohtas Sasaram(bihar)
Faculity of law
Topic- Sampling
Presented By- Aditya Nandan
22BBL013
1st SEMESTER
Guided By- Sanjay kumar singh
Assistant professor…

2. SAMPLING
The process of selecting a number of individuals for a study in such a way that
the individuals represent the larger group from which they were selected.

3. Types of sampling
 Probability Sampling
 Non probability Sampling

4. 1. Probability Sampling
 Best method to achieve a representative sample.
 Four techniques
1. Random
2. Stratified random
3. Cluster
4. Systematic

5. Selecting Random Samples
1. Random sampling
Selecting subjects so that all members of a population have an equal and independent chance of
being selected.
 Advantages
1. Easy to conduct.
2. High probability of achieving a representative sample.
3. Meets assumptions of many statistical procedures.
 Disadvantages
1. Identification of all members of the population can be difficult.

6. Selecting Random Samples
2. Stratified random sampling
 The population is divided into two or more groups called strata, according to same criterion ,such
as geographic location, grade level, age, or income and subsamples are randomly selected from
each strata.
 Advantages
1. More accurate sample
2. Can be used for both proportional and non proportional sample
3. Representation of sub groups in the sample
 Disadvantage
1. Identification of all members of the population can be difficult.

7. Selecting Random Samples
3. Cluster sampling
 The process of randomly selecting intact groups, not individuals, within the defined
population sharing similar characteristics.
 Advantages
 Very useful when populations are large and spread over a large geographic region
 Convenient and expedient.
 Disadvantages
 Representation is likely to become an issue.

8. Selecting Random Samples
4. Systematic sampling
 Selecting every Kth subject from a list of the members of the
population.
 Advantage
 Very easily done
 Disadvantages
 Subgroups
 Some members of the population don’t have am equal.

9. Stratified Random sampling
Stratified random sampling is a method of sampling that involves the
division of a population into smaller subgroups known as strata. In
stratified random sampling, or stratification, the strata are formed based
on members' shared attributes or characteristics, such as income or
educational attainment.

10. Systematic sampling
Systematic sampling is a probability sampling method where researchers select
members of the population at a regular interval – for example, by selecting
every 15th person on a list of the population. If the population is in a random
order, this can imitate the benefits of simple random sampling.

11. Cluster sampling
Cluster sampling is a probability sampling method in which you divide a
population into clusters, such as districts or schools, and then randomly
select some of these clusters as your sample. The clusters should ideally each
be mini-representations of the population as a whole.

12. 2.Non probability sampling
 Non-probability sampling is a method of selecting units from
a population using a subjective (i.e. non-random) method.
Since non-probability sampling does not require a complete
survey frame, it is a fast, easy and inexpensive way of
obtaining data.

13. Convenience sampling
Convenience sampling is a non-probability sampling method where
units are selected for inclusion in the sample because they are the
easiest for the researcher to access. This can be due to geographical
proximity, availability at a given time, or willingness to participate in the
research.

14. Judgmental sampling, also called purposive sampling or authoritative
sampling, is a non-probability sampling technique in which the sample
members are chosen only on the basis of the researcher's knowledge and
judgment.
Judgement sampling

15. Quota sampling
Quota sampling is a non-probability sampling method that relies on the non-
random selection of a predetermined number or proportion of units. This is called
a quota. You first divide the population into mutually exclusive subgroups (called
strata) and then recruit sample units until you reach your quota.

16. Snowball sampling is a non-probability sampling method where new units are
recruited by other units to form part of the sample. Snowball sampling can be a
useful way to conduct research about people with specific traits who might
otherwise be difficult to identify (e.g., people with a rare disease)
Snowball sampling