Sampling design is vital in research for selecting representative subsets of populations, enabling cost-effective, timely, and feasible data collection while enhancing accuracy. The document outlines various sampling techniques, including probability and non-probability methods, and factors influencing sample size, such as population size and variance. It also emphasizes the risks of sampling bias and the importance of ethical considerations, including informed consent and confidentiality.

1. Introduction to
Sampling Design
Sampling design is an essential part of research. It involves selecting
a representative subset of a population for study. This allows
researchers to draw conclusions about the entire population without
having to study every individual.
SS
by Siva Gurunathan S
Assistant Professor,
PG and Research Department of Economics,
Sacred Heart College (Autonomous),
Tirupattur-635601.

2. Importance of Sampling in
Research
1 Cost-effectiveness
Studying a sample is often
more efficient and
affordable than studying
the entire population.
2 Time efficiency
Collecting data from a
sample is generally quicker
than collecting data from
the entire population.
3 Feasibility
In many cases, it is
impossible to study every
individual in a population.
For example, it would be
impossible to interview
every person in the United
States.
4 Accuracy
When done properly,
sampling can provide
accurate results that are
representative of the entire
population.

3. Types of Sampling Techniques
Probability Sampling
Each member of the population has a known chance of
being selected for the sample.
Non-Probability Sampling
The selection of participants is not based on chance. The
researcher makes subjective choices about who to
include in the sample.

4. Probability Sampling
Methods
Simple Random
Sampling
Every member of the
population has an equal
chance of being selected.
Stratified Random
Sampling
The population is divided
into subgroups (strata), and
a random sample is selected
from each stratum.
Cluster Sampling
The population is divided
into clusters, and a random
sample of clusters is
selected.
Systematic Sampling
Every kth member of the
population is selected,
where k is a predetermined
interval.

5. Non-Probability Sampling
Methods
Convenience Sampling Participants are selected based
on their availability and ease of
access.
Quota Sampling The sample is selected to reflect
the proportions of different
subgroups in the population.
Purposive Sampling Participants are selected based
on their specific characteristics
or expertise.
Snowball Sampling Participants are asked to refer
other participants who meet the
study criteria.

6. Sample Size Determination
1 Population size
The larger the population, the larger the sample size needs to be.
2 Desired margin of error
A smaller margin of error requires a larger sample size.
3 Confidence level
A higher confidence level requires a larger sample size.
4 Population variability
A more variable population requires a larger sample size.

7. Sampling Bias and Errors
Selection Bias
Occurs when the sample is not representative of the
population.
Nonresponse Bias
Occurs when some participants refuse to participate in
the study.
Measurement Bias
Occurs when the measurement instrument is not
accurate or reliable.

8. Sampling Frame and
Accessibility
Sampling Frame
A list of all individuals in the
population.
Accessibility
The ability to reach and contact
individuals in the population.
Permissions
Obtaining consent from
individuals before collecting
data.
Privacy
Protecting the confidentiality of
participant data.

9. Ethical Considerations in Sampling
1 Informed consent
Participants must be fully informed about the study
and give their consent to participate.
2 Confidentiality
Participant data must be kept confidential and not
shared with unauthorized individuals.
3 Beneficence
The study should benefit participants and society.
4 Justice
The benefits and risks of the study should be
distributed fairly among participants.

10. Conclusion and Key
Takeaways
Sampling design is a crucial aspect of research. Choosing the right
sampling technique and determining the appropriate sample size
are essential for obtaining accurate and meaningful results. It's
important to be aware of potential biases and errors in sampling and
to adhere to ethical guidelines when conducting research.