Statistics and its topic of sampling distribution. Two types of distribution.

1. Made By:
Krutika Pachauri
Aathira Sugathan
Ruturaj Bhopatrao
Amit Sakore
Rahul Kumar

2. Sampling
Definition:
A process in which fixed numbers of observations are taken randomly from
a large population.
According to Cocharn “In every branch of science lack the resources, to
study more than a fragment of the phenomena that might advance our
knowledge.”
According to Davis S. Fox “ In the social science, it is not possible to collect
data from every respondent relevant to our study but only from some
fractional part is called sampling.”

3. Basic Concepts of Sampling
Basic
concepts of
sampling
Universe/
Population
Samples
Statistical
Population
Sampling
Frames
Parameter(s)
and
Statistics(s)

4. •Universe: Sum total of objects under study, both animated inanimated.
•Statistical Population: The total of quantities that are measurable or set of
numbers.
•Samples: Part of the population which is examined to estimate the characteristics
of the population.
•Sampling Frame: Actual set of units analyst containing every member of the
population from which a sample is drawn at random.
•Parameter(s): A characteristic of a population.
•Statistic(s): A characteristic of a sample.

5. Objectives of sampling
•Statistical Estimation
•Testing of Hypothesis
•Statistical Inference
•Quality Control

6. Sampling Design Process
A brief description of measurements will be taken at what times , on which
material , in what manner , and by whom.
•Sampling plan
Define the
Universe
Sample Frame
Specifying
Sampling Units
Selection of
Sample Design
Determination
of Sample size
Select the
sample

7. Characteristics of a good sample
1. Accurate.
2. Economical.
3. Good Size.
4. Feasible.
5. Practical.
6. Free from bias.

8. Uses of Sampling
1. Large population is covered adequately.
2. A lot of energy money and time is saved.
3. Can be used when data is unlimited.
4. When units are relatively homogeneous then sampling techniques become
very useful.
5. When 100% accuracy is not required.

9. Advantages
1. Saves money, time and effort.
2. More effective.
3. Faster and cheaper.
4. More accurate.
5. Gives more comprehensive information

10. Disadvantages
1. Biased selection.
2. Difficulty in selection.
3. Specialized knowledge needed.
4. Problem of cooperation.
5. Less accuracy.
6. Limited nature.

11. Types of sampling techniques
Types of
Sampling
Techniques
Probability
Sampling
Non
probability
Sampling

12. Types of
probability
sampling
Simple random
sampling
Stratified
random
sampling
Multi-stage
sampling
Systematic
sampling
Cluster
Sampling
Area sampling

13. Types of Non
probability
Sampling
techniques
Convenience
sampling
Panel Sampling
Purposive
Sampling
Snowball
Sampling

14. Difference between Probability and
Non-probability Sampling
•Control
•Chances of selection bias
•Economy
•Reliability
•Suitability
•Degree of accuracy
•Sampling Frame
•Convenience