It will be useful for master students quantitative method. It consist sample definition, purpose of sampling, stages in the selection of a sample, types of sampling in quantitative researches. Thank you

1. By: Puneet Gupta
M.Tech (Future Studies and Planning)

2. 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. Sampling…….
SAMPLE
STUDY POPULATION
TARGET POPULATION

4.  A sample is “a smaller collection of units from a
population used to determine truths about that
population”
 The sampling frame
A list of all elements or other units containing the
elements in a population.

5. Population…
…the larger group from which
individuals are selected to
participate in a study

6. Why Sample?
Get information about large populations
Lower cost
More accuracy of results
High speed of data collection
Availability of Population elements.
Less field time
When it’s impossible to study the whole population

7. Define the target population
Select a sampling frame
Conduct fieldwork
Determine if a probability or nonprobability
sampling method will be chosen
Plan procedure for selecting
sampling units
Determine sample size
Select actual sampling units
Stages in the
Selection
of a Sample

8. The sample must be:
1. representative of the population;
2. appropriately sized (the larger the better);
3. unbiased;
4. random (selections occur by chance);
What is Good Sample?

9. •Probability sample – a method of sampling that uses of
random selection so that all units/ cases in the population
have an equal probability of being chosen.
• Non-probability sample – does not involve random
selection and methods are not based on the rationale of
probability theory.
Types of Sampling
Sampling
Techniques
Probability
Non-
Probability

10. Simple random sample
Systematic random sample
Stratified random sample
Cluster sample
Probability (Random) Samples

11. Non-Probability Samples
– Convenience samples (ease of access)
sample is selected from elements of a population
that are easily accessible
– Purposive sample (Judgmental Sampling)
You chose who you think should be in the study
– Quota Sampling
– Snowball Sampling (friend of friend….etc.)

14. SIMPLE RANDOM SAMPLING
• Applicable when population is small, homogeneous &
readily available
• All subsets of the frame are given an equal probability.
Each element of the frame thus has an equal probability
of selection. A table of random number or lottery system
is used to determine which units
are to be selected.

15. Advantages:
 Minimal knowledge of population needed
 Easy to analyze data
Disadvantages:
 Low frequency of use
 Does not use researchers’ expertise
 Larger risk of random error

16. Simple random sampling
Every subset of a specified size n from the population
has an equal chance of being selected
Sunil Kumar

17. • Similar to simple random sample. No table of random
numbers – select directly from sampling frame. Ratio
between sample size and population size
• Then every nth number on the list is selected
• N= Sampling Interval
Systematic Sampling

18. Advantages:
 Moderate cost; moderate usage
 Simple to draw sample
 Easy to verify
Disadvantages:
 Periodic ordering required

19. Systematic sampling
Every member ( for example: every 20th person) is
selected from a list of all population members.

20.  The population is divided into two or more groups
called strata, according to some criterion, such as
geographic location, grade level, age, or income.
 Subsamples are randomly selected from each strata.
Sunil Kumar

21. Advantages:
 Assures representation of all groups in
sample population
 Characteristics of each stratum can be
estimated and comparisons made
Disadvantages:
 Requires accurate information on proportions
of each stratum
 Stratified lists costly to prepare

22.  Cluster sampling is an example of 'two-stage sampling' .
 First stage a sample of areas is chosen;
 Second stage a sample of respondents within those areas
is selected.
 Population divided into clusters of homogeneous units,
usually based on geographical contiguity.
 Sampling units are groups rather than individuals.
 A sample of such clusters is then selected.
 The population is divided into subgroups (clusters) like
families. A simple random sample is taken of the
subgroups and then all members of the cluster selected
are surveyed

23. Advantages:
 Can estimate characteristics of both cluster and
population
Disadvantages:
 The cost to reach an element to sample is very high
 Each stage in cluster sampling introduces sampling
error—the more stages there are, the more error
there tends to be

24. Section 4
Section 5
Section 3
Section 2Section 1

26. Convenience sampling involves choosing respondents at
the convenience of the researcher.
Advantages
 Very low cost
 Extensively used/understood
Disadvantages
 Variability and bias cannot be measured or
controlled
 Projecting data beyond sample not justified
 Restriction of Generalization.

27. CONVENIENCE SAMPLING

28. The population is first segmented into mutually
exclusive sub-groups, just as in stratified sampling.
Advantages
 Used when research budget is limited
 Very extensively used/understood
 No need for list of population elements
Disadvantages
 Variability and bias cannot be measured/controlled
 Time Consuming
 Projecting data beyond sample not justified

30. Researcher employs his or her own "expert”
judgment about.
Advantages
 There is a assurance of Quality response
 Meet the specific objective.
Disadvantages
 Bias selection of sample may occur
 Time consuming process.

31. The research starts with a key person and introduce
the next one to become a chain
Advantages
 Low cost
 Useful in specific circumstances & for locating
rare populations
Disadvantages
 Not independent
 Projecting data beyond sample not justified

32. SNOWBALL SAMPLING