Meaning & Definition of Population & Sampling, Types of Sampling - Probability & Non-Probability Sampling Techniques, Characteristics of Probability Sampling Techniques, Types of Probability Sampling Techniques, Characteristics of Non-Probability Sampling Techniques, Types of Non-Probability Sampling Techniques, Errors in Sampling, Size of sample, Application of Sampling Technique in Research
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Population and Sampling.pptx
1. Population and Sampling
M.VIJAYALAKSHMI
M.Sc. (Life Sci.), M.Phil. (Life Sci.), M.Ed., M.Phil. (Education), M.Sc. (App. Psy.),
NET (Edn), PGDBI
Assistant Professor in Education
Avinashilingam Institute for Home Science and Higher Education for Women
Coimbatore - 641043
2. Population and Sampling
Meaning & Definition of Population & Sampling,
Types of Sampling - Probability & Non-
Probability Sampling Techniques, Characteristics
of Probability Sampling Techniques, Types of
Probability Sampling Techniques, Characteristics
of Non-Probability Sampling Techniques, Types of
Non-Probability Sampling Techniques, Errors in
Sampling, Size of sample, Application of Sampling
Technique in Research
3. General Learning Objectives
The teacher-trainees -
Acquires the knowledge of the Population & Sampling
Comprehends the Types of Sampling
Understands about the Characteristics of Probability &
Non-Probability Sampling Techniques
Recognizes the Types of Probability & Non-Probability
Sampling Techniques
Acquires the skills to find out the Errors in sampling
Analyses the Size of sample
Identifies the Application of Sampling Technique in
Research
4. Learning Outcomes
At the end of the course, the teacher-trainees will be able to:
describe the meaning and definition of Population and Sampling
explain about the types of Sampling Techniques
portray the characteristics of Probability Sampling Techniques
classify the different types of Probability Sampling Techniques
list down the characteristics of Non-Probability Sampling Techniques
categorize various types of Non-Probability Sampling Techniques
compare Probability and Non-Probability Sampling Techniques
differentiate Probability and Non-Probability Sampling Techniques
elucidate about the Parameter and Statistic
examine the Sampling error and Sampling Bias
determine the Sample Size
point out the application of Sampling Technique in research
5. Meaning & Definition of Population
• Population is the target group which a
researcher selected to draw a conclusion
about it.
• Group of individuals who have common
characteristics.
• Size of the population.
6. Meaning & Definition of Sample
• Subset of a population.
• Samples are used in
research in order to draw
inferences about population.
• Size of the sample.
9. Probability Sampling Techniques
• Employs random sampling techniques to
create a sample.
• Every individual of the population has an
equal probability to be selected as the sample.
• It is a true representation of the population.
10. Characteristics of
Probability Sampling Techniques
All the individuals in the population get an equal chance to
be selected as a sample.
It is a true representation of the sample.
Basis of selection is done randomly.
Opportunity of selection of the sample is fixed and known.
Used mostly in conclusive research.
Results are unbiased.
Method of selection is objective.
Inferences are drawn statistically.
Hypotheses are tested.
Time consuming process.
12. Simple Random Sampling
Every individual in the
population has an equal
chance for being a sample
They are having
independent chance
of being selected
Lots system, coin-tossing, dice-throwing, lottery method, etc.
13. Systematic Sampling
Selecting every Kth individual of the population.
First individual is selected randomly. Others are
selected systematically by using a formula
K = N/n.
K – Sampling interval; N – Population (20);
n – Sample (5).
20/5 = 4. Every 4th individual is selected.
15. Cluster Sampling
Group 2
(English)
Group 1
(Tamil)
Group 4
(Biological
Science)
Sample
Groups are formed - Clusters. Then the clusters are selected randomly
Group 3
(Mathematics)
Group 5
(Physical
Science)
Group 6
(History)
16. Sub-types of Cluster Sampling
Single Stage Cluster Sampling
Two Stage Cluster Sampling
Entire cluster is
selected randomly
for sampling
From the randomly selected
clusters, we randomly select
individuals for sampling
17. Multi-stage Sampling
Multistage sample Population
(B.Ed. )
Multiple clusters
(Pedagogy )
Stratum/Sub groups
(English/Tamil Medium)
Cluster
(All pedagogy, English Medium)
Individual
18. Non-Probability /
Purposive Sampling Techniques
o Uses non-random processes
o Researcher chooses the sample arbitrarily.
o It is not known that which individual from the
population is going to be selected for a sample.
o It is not a true representation of the population.
19. Characteristics of
Non-Probability Sampling Techniques
All the individuals in the population do not get an equal
chance to be selected as a sample.
It is not a true representation of the sample.
Basis of selection is done non-randomly.
Opportunity of selection of the sample is not specified and
unknown.
Used widely in exploratory research.
Results are biased.
Method of selection is subjective.
Inferences are drawn analytically.
Hypotheses are generated.
Quick and easy process.
23. Quota Sampling
This type of sampling depends on some pre-set standard.
Proportion of characteristics/ trait in sample should be same as
population.
Example, in a B.Ed. Class, quota is done according to their
pedagogy subject.
Stratified
sample
Proportion
Judgement
Quota is fixed
26. Probability Sampling vs
Non-Probability / Purposive Sampling
Probability Sampling Non-Probability / Purposive Sampling
Inferences about the entire
population is available
Inferences about the entire population is
not available
Randomly selected Non-Randomly selected
Inferences are generalized Inferences are non-generalized
Expensive and time consuming
process
Less expensive and more convenient
process
Less chances to bias and sampling
errors
Chances for bias and Sampling errors
27. Parameter and Statistic
• A parameter is a measure that describes the
whole population.
• A statistic is a measure that describes the
sample.
28. Errors in Sampling
A sampling error is the difference between a
population parameter and a sample statistic.
Sampling error reduces when the sample size
increases.
Sampling errors and biases are induced by the sample
design. They include:
Selection bias
Random sampling error
29. Non-sampling error
Errors not related to the act of selecting a sample
from the population. They can even be present in
census.
Non-sampling errors are:
o Over-coverage
o Under-coverage
o Measurement error
o Processing error
o Non-response or Participation bias
Two major types of non-response are:
Unit non-response
Item non-response
30. Size of sample
• Number of individuals in the sample is called
as size of the sample.
• A sampling frame is a list of all the units in
the population from which a sample will be
selected.
31. Calculation of Sample Size
• To calculate the sample size, you need the following
parameters.
– Z-score
– Standard deviation
– Margin of error (0.05, 0.01)
– Confidence level (95%, 99%)
To calculate the sample size, use this formula:
Sample Size = (Z-score)2 * StdDev*(1-StdDev)
(Margin of error)2
32. Application of
Sampling Technique in Research
Used to make inferences about populations.
Cost-effective
Less time consuming in sampling
Scope of sampling is high
Accuracy of data is high
Convenient
Practical
Manageable
Intensive and exhaustive data
Suitable in limited resources
Better rapport
33. Recapitulation
Meaning & Definition of
Population & Sampling
Types of Sampling
Probability & Non-Probability Sampling Techniques
Characteristics of
Probability & Non-Probability Sampling Techniques
Types of Probability & Non-Probability Sampling Techniques
Errors in Sampling
Size of sample
Application of Sampling Technique in Research
34. References
• Kothari., C.R. (2019). Research Methodology: Methods and Techniques
(4th Multi Colour ed.). New Delhi: New Age International Publishers.
• Methods of sampling from a population. In Health Knowledge. Retrieved
June 8, 2020, from https://www.healthknowledge.org.uk/public-health-
textbook/research-methods/1a-epidemiology/methods-of-sampling-
population
• Sample Size Calculator. In Calculator. Retrieved June 8, 2020, from
https://www.calculator.net/sample-size-calculator.html
• Sampling (statistics). In Wikipedia. Retrieved June 8, 2020, from
https://en.wikipedia.org/wiki/Sampling_(statistics)
• Sampling bias: What is it and why does it matter? In Scribbr. Retrieved
June 8, 2020, from https://www.scribbr.com/methodology/sampling-bias/
• Types of Sampling: Sampling Methods with examples. In Questionpro.
Retrieved June 8, 2020, from https://www.questionpro.com/blog/types-of-
sampling-for-social-research/
• Understanding different sampling methods. In Scribbr. Retrieved June 8,
2020, from https://www.scribbr.com/methodology/sampling-methods/