SAMPLING Need, Types, Significance and Methods

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from the Department of Geography, Malda College
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2. Skill Development Course
on
Data Collection, Representation and Analysis
in Social Science
[ February 21, 2021 to April 18, 2021 ]
Organised By
Department of Geography
Malda College (University of Gour Banga)
2nd Lecture

3. SAMPLING
Need, Types, Significance and Methods
Mithun Ray
Department of Geography
Malda College (University of Gour Banga)
E-mail: mithun.ray147@gmal.com

4. SAMPLING
is a technique of selecting individual members or a
subset of the population to make inferences from them
and estimate characteristics of the whole population.

5. FUNDAMENTAL CONCEPTS IN
SAMPLING
I. POPULATION / UNIVERSE:
Any group of people or objects that form the
subject of study in a particular survey

6. Is there any difference between
POPULATION and UNIVERSE !
‘YES’
All units in any field of inquiry constitute UNIVERSE
and
All elementary units constitute POPULATION

7. POPULATION
HOMOGENEOUS HETEROGENEOUS

8. HOMOGENEOUS
POPULATION
In terms of Gender

9. HETEROGENEOUS
POPULATION
In terms of Gender

10. II. ELEMENT
An element comprises a single member of the population

11. III. SAMPLING FRAME
Comprises all the elements of a population with proper
identification that is available for selection at any stage of
sampling
Voter List- an example of Sampling Frame

12. IV. SAMPLE
It is a subset of the population. It comprises only some
elements of the population
Reference: https://www.scribbr.com/methodology/sampling-methods/

13. V. CENSUS
Complete enumeration of all items in the population

14. VI. STATISTIC(S)
VII. PARAMETER (S)
is a characteristic of
the sample
is a characteristic of the population

15. Sample Size
Online sample size calculator http://www.raosoft.com/samplesize.html
The size of a sample depends upon the basic characteristics
of the population, the type of information required from the
survey and the cost involved.
Small Sample = < 30
Large Sample = ≥ 30

16. USES OF SAMPLING IN DAILY LIFE
3 EXAMPLES…

17. EXAMPLE 1

18. EXAMPLE 2

19. EXAMPLE 3

20. এোর কোমাজের িাোর োো !!!

21. NEED FOR SAMPLING
I. Economic Advantage
II. The Time Factor
 Can save time:
Example: If a Researcher wants to know the food habit of
people live in Haldibari Municipality. According to Census of
India, 2011 total population is 14404 persons.
Is it possible to survey each person !
Yes, but time to be taken to conduct this survey will be more than
2 years (suppose number of persons surveyed daily is 20)
Indian Census, 2011: Rs. 7000 Crore
Indian Census, 2021: Rs. 3768 Crore (allocated)
 When information urgently required:
Example: Covid-19

22. III. The
destructive
nature of the
observation
Photographic Film
To test the quality of a fuse, to determine
whether it is defective, it must be destroyed
Electrical Fuse
To test the quality of
Photographic Film it
needs to expose
completely and the
moment it is exposed
it gets destroyed

23. IV. ACCURATE AND RELIABLE RESULTS
 Samples can yield reasonably accurate
information
 The study of sample instead of complete
enumeration may, at times, produce more reliable
results.

24. V. THE PARTLY ACCESSIBLE POPULATIONS
There are some populations that are so difficult to get
access to that only a sample can be used.
An Example

25. SAMPLING DESIGN
The process of selecting samples from a population
or
A definite plan for obtaining a sample from a given population

26. CHARACTERISTICS OF A GOOD
SAMPLE DESIGN
 Must result in truly representative sample
 Must be such which results in a small sampling error
 Must be viable in the context of funds available for
the research study

27. TYPES OF SAMPLING
A. Based on Element Selection Technique
i. Restricted Sampling: Elements are chosen using a
specific methodology
ii. Unrestricted Sampling: Elements are selected
individually and directly from the population

28. B. Based on Representation
i. Probability Sampling:
Each and every element of the population has a known
chance of being selected in the sample
ii. Non-probability Sampling:
The elements of the population do not have any known
chance of being selected in the sample

29. Probability Sampling
Simple Random
Sampling
Systematic
Sampling
Cluster
Sampling
Stratified
Sampling
Multi-stage
Sampling

30. Simple Random Sampling
Each element of the frame has an equal probability of
selection

31. Reference: https://www.questionpro.com/blog/simple-random-sampling/

33. Simple Random Sampling with Replacement

34. Simple Random Sampling without Replacement

35. Suitability
This method is suitable for small homogeneous population
Drawback
In case of large sampling frame this method is impracticable
Simple Random Sampling

36. Systematic Sampling
The entire population is arranged in a particular order
according to a design
Reference: https://www.scribbr.com/methodology/sampling-methods/

37. In a systematic sampling the first unit of sample is selected at
random and having chosen this there is no control over the
subsequent units of sample. Due to this reason, it is at times
referred as mixed sampling
K = N/n
Where,
K = sampling interval
N = size of the
population
n = size of the
sample

38. Stratified Sampling
The entire population is divided into strata (groups) which
are mutually exclusive and collectively exhaustive.
Example: age, gender, income, education etc.
Reference: https://www.scribbr.com/methodology/sampling-methods/

40. Relevant questions in the context of
Stratified Random Sampling
Q.1: What criteria should be used for stratifying the
universe ?
Q. 2: How many strata should be constructed ?
Q. 3: What should be appropriate number of sample
size to be taken in each stratum ?
Proportionate
or
Disproportionate

41. Proportionate Allocation Scheme
The size of the sample in each stratum is proportional to the
size of the population of the strata
n1= n ×
N1
N
Where,
n1= Sample Size from a stratum
n = Total Number of Sample
N1= Total elements in the stratum
N = Total Population
Disproportionate Allocation Scheme

42. Cluster Sampling
The entire population is divided into various clusters in such a
way that the elements within the clusters are heterogenous.
However, there is homogeneity between the clusters.

43. Steps in Cluster Sampling
Reference: https://www.scribbr.com/methodology/cluster-sampling/

46. Reference: https://www.scribbr.com/methodology/cluster-sampling/

47. Area Sampling
If clusters happen to be some geographic subdivisions, in
that case cluster sampling is better known as area sampling.

48. Multi-stage Sampling
is a further development of the principle of cluster sampling
State District Block Village

49. Probability Sampling
Simple Random
Sampling
Systematic
Sampling
Cluster
Sampling
Stratified
Sampling
Multi-stage
Sampling

50. Non-probability Sampling
CONVENIENCE
SAMPLING
SNOWBALL
SAMPLING
QUOTA
SAMPLING
JUDGEMENTAL
SAMPLING

51. CONVENIENCE SAMPLING
The only criterion for selecting sampling units in this
scheme is the convenience of the researcher or the
investigator.

52. Example of Convenience Sampling
Interviews conducted by a TV channel of people coming out of a
cinema hall, to seek their opinion about the movie

53. Source: https://www.questionpro.com/blog/convenience-sampling/
This sampling design is often used in the pre-test phase of
a research study such as the pre-testing of a questionnaire.

54. PURPOSIVE / JUDGEMENTAL SAMPLING
Source: https://research-methodology.net/sampling-in-primary-data-collection/purposive-sampling/
Experts in a particular field choose what they believe to be the
best sample for the study in question

55. Example of Judgmental Sampling

56. QUOTA SAMPLING
Source: https://www.slideshare.net/Kenisha7/quota-and-snowball
The samples includes a minimum number from each specified
subgroup in the population. The sample is selected on the
basis of certain demographic characteristics such as age,
gender, occupation, education, income, etc.

57. Example
Job satisfaction level among the employees of Malda College
Group D
Group C
Assistant Professor
Associate Professor

58. * The investigator are assigned quotas of the sample to be
selected satisfying the required characteristics
** Quota Sampling does not require a sampling frame
*** In Stratified Sampling, the selection of sample from each
stratum is random but in the quota sampling, the
respondents may be chosen at the convenience or
judgement of the researcher
Points to be noted

59. SNOWBALL SAMPLING
 Research participants recruit other participants for a test or
study
 It is used where potential participants are hard to find.
Source: https://www.questionpro.com/blog/snowball-sampling/

60. Types of Snowball Sampling
1. Linear Snowball Sampling
2. Exponential Non-Discriminative Snowball Sampling
3. Exponential Discriminative Snowball Sampling

61. SAMPLING
PROBABILTY NON-
PROBABILITY
SIMPLE RANDOM
SAMPLING
STRATIFIED RANDOM
SAMPLING
CLUSTER
SAMPLING
SYSTEMATIC
SAMPLING SNOWBALL
SAMPLING
QUOTA
SAMPLING
PURPOSIVE /
JUDGEMENTAL
SAMPLING
CONVENIENCE
SAMPLING

62. Sampling Error
A sampling error occurs when the sample used in the study
is not representative of the whole population.
Source: https://www.questionpro.com/blog/sampling-error/

63. Summary
Sampling
Fundamental Concepts in Sampling
 Need for Sampling
 Types of Sampling

64. This Power Point Presentation (PPT) has been
prepared only to deliver the lecture. The
materials (Maps, Diagrams and Images) used in
this presentation have been collected and
compiled by the presenter from various
academic blogs, research papers, books etc.

65. THANK YOU