The document discusses different sampling methods used in statistics. It defines key terms like population and sample. It describes probability sampling methods like simple random sampling, stratified random sampling, and cluster sampling which give each unit an equal chance of selection. It also covers non-probability sampling techniques like convenience sampling which do not guarantee equal selection probability. The advantages and disadvantages of different approaches are provided.

2. Population is defined as
the entire mass of
observation, which is the
parent group from which
a sample is to be formed.
Sample is defined as the
aggregate of objects,
person or elements,
selected from the
universe.

3. Sampling- The method of taking the
sample is known as sampling.

4. Economical
Importance of
Sampling
Accuracy
Save time
and
efforts
Easily
approachable
Practical
Errors can
be
controlled

5. Sampling
Probability
Non
Probability

6. Probability sampling
• Every unit of the
population has an
equal chance of being
selected for the
sample.
Non probability
sampling
• Sampling techniques
one cannot estimate
beforehand the
chance of each
element being
included in the
sample.

7. Simple random sampling
Stratified random sampling
Systematic sampling
Cluster sampling
Multi-stage sampling

8. Random sampling is applied when the
method of selection assures each
individual element in the universe an
equal chance of being chosen.

9. Conjunction
with other
methods
Advantages
unbiased
Easy to find
errors
Equal
chance

10. Consumes
time and
energy
More
chances of
misleading
sample
Difficult for
comparison
study

11. Lottery Method
Tippet’s Number
Grid method

12. Stratified sampling - When the population is
divided into different strata then samples are
selected from each stratum by simple random
sampling or by regular interval method we call
it as stratified random sampling method.

13. Advantages
•Comparing sub-categories
•Save time, money
and energy
•Can represent
various group

14. Requires more efforts
Needs a larger sample size
Strata are overlapping, chances of bias

15. Stratified sampling
Disproportionate sampling
Proportionate sampling

16. Systemic sampling - This sampling is obtaining
a collection of elements by drawing every nth
person after that; n is a number termed as
sampling interval.

17. Advantages
•Easy to use
Disadvantages
•Over representation of several groups
is greater.

18. Cluster Sampling- The whole population is
surveyed and such areas are located
wherein elements are seen clustering
themselves and sample is selected from
such clusters and they reflect all
characteristics of the Universe.

19. Advantages
Easier to apply larger Geographical area
Save time of travelling

20. Disadvantages
Not good representative of the
population
Sampling error
Same individual can belong to
two clusters and studied twice

21. Multi stage sampling sample is selected
in various stages but only last sample is
studied.

22. Advantages
•Good representative of population
•Improvement of other sampling methods
Disadvantages
•Difficult and complex method

23. Non probability Sampling- One cannot estimate
beforehand the probability of each element being
included in the sample. It also does not assure that
every element has a chance of being included.

24. Incidental/ Accidental sampling
Convenience sampling
Purposive sampling
Quota sampling

25. Incidental or
Accidental sampling
means selecting the
units on basis of easy
approaches.

26. Advantages
• Easy and quick results
• Saves time, money and
energy
Disadvantages
• Not representative of
population
• Cannot produce reliable
results

27. In Convenience method, the investigator
selects certain items are to his
convenience. No pre planning is
necessary for the selection of items.

28. disadvantages
• Biased data
• Not
representative
population
Advantages
• Easy method
• Economical

29. Purposive sampling- The selection
of elements is based upon the
judgement of the researcher, the
purposive sampling is called
judgement sample

30. Advantages
•Control on variable
Disadvantages
•Reliability of criterion
is questionable

31. Quota sampling:-In the quote
sampling the interviewers are
instructed to interview a specified
number of persons from each
category.

32. • Practical
Advantages • Economical
• Not true
representative
• Not free from error
disadvantages

33. Errors
Sampling
Errors
Biased
errors
Unbiased
errors
Non Sampling
Errors

34. Technique Strength Weakness
Probability
Simple Random Sampling Easily understood, results
projectable
Expensive, assurance of
representative
Stratified sampling Include all important sub
populations
Expensive, Difficult to
select relevant
stratification variables
Systemic sampling Increase
representativeness
Can decrease
representative
Cluster sampling Easy to implement, cost
effective
Difficult to interpret
results
Non probability
Convenience sampling Least expensive, least
time consuming.
Quota sampling Sample can be controlled
for certain characteristics
Bias, no assurance of
representative

35. Choosing non Probability vs. Probability sampling
Conditions favouring the use of
Factors Non probability
sampling
Probability sampling
Nature of research Exploratory Conclusive
Relative magnitude of
Non sampling errors
sampling and non
are larger
sampling errors
Sampling errors are
larger
Variability in the
population
Homogeneous Heterogeneous
Statistical consideration Unfavourable Favourable
Operational
considerations
Favourable Unfavourable