1. Sampling
Chapter 5

2. Meaning
Selection of some part of an aggregate or total on the basis of which a judgment about the aggregate or total is made
Process of obtaining information about an entire population by examining only a part of it

3. SAMPLING…….
STUDY POPULATION
SAMPLE
TARGET POPULATION

4. Essentials or characteristics of a good sample
Representativeness
Sample must be representative of the entire population
Accuracy
Must result in very small error
Economy
Viable in the context of funds available
Size

5. Factors affecting Sample size
Nature of Universe
Whether universe is homogenous or heterogeneous
Dispersion factor
Size of Population
Nature of study
For intensive and continuous studies, small size is appropriate
Type of Sampling
With random sample, small size also may be allowed
Standard of Accuracy and acceptable confidence level
Availability of finance

6. Non Probability Sampling
Sampling Methods
Probability Sampling
Non Probability Sampling

7. Simple Random Sampling
Probability Sampling
Each unit should have a known chance of being selected in the population
Cluster Sampling
Simple Random Sampling
Systematic Sampling
Stratified Sampling

8. Simple Random Sampling
Applicable when population is small, homogeneous & readily available.
Each element has an equal probability of selection.
A table of random numbers or computer generated random numbers can be used.
Method impractical with large samples

9. Systematic Sampling An alternative to random sampling
Selection of first unit is on random basis
Remaining units selected at fixed intervals
Steps
Number of units in the population-N
Sample size –n
Interval size –k =N/n
Select the first unit randomly
Select every kth unit

10. Stratified Sampling
Involves dividing the population into homogenous sub groups and then taking simple random sample in each subgroup
Stratification improves sample’s representativeness

11. Cluster Sampling
Divide the population into a number of non-overlapping areas (clusters)
Randomly select a number of these clusters
Measure all units within selected clusters
Two types
Area Sampling- Clusters happen to be geographic subdivisions
Multi stage Sampling-Clusters formed at in different stages, applicable to inquiries extending to large geographical areas

12. Non Probability Sampling Methods
Method does not adopt any basis for estimating the probability that each item in the population has to be included in the sample
Methods
Convenience Sampling
Purposive or Judgment Sampling
Quota Sampling
Snowball Sampling

13. Convenience Sampling
Sometimes known as grab or opportunity sampling or accidental or haphazard sampling
Sample drawn from that part of the population which is close to hand
Most useful for pilot testing

14. Purposive or Judgment Sampling
Deliberate selection of sample units that conform to some pre determined criteria
Selection of those samples that are considered most appropriate ones for the study
Based on the judgment of the researcher

15. Quota Sampling Selecting people non randomly based on some fixed quota
Two types
Proportional
Non proportional
Not aimed at precision but need results quickly

16. Snowball Sampling Identify those who meet the criteria of study
Ask them to recommend others who meet the criteria
Method suitable when population is difficult to find

17. Thank You