0BJECTIVES
- Understand the purpose and importance of sampling in research.
- Differentiate between probability and non-probability sampling methods.
- Identify scenarios where each technique is appropriate.
- Evaluate the strengths, weaknesses, and biases associated with different sampling techniques.
Techniques of Sampling: Probability and Non-Probability Sampling
Sampling is a fundamental process
in research methodology. It allows researchers to make inferences about a
population by studying a subset of it. Sampling techniques are broadly
categorized into probability sampling and non-probability sampling,
each serving distinct research purposes and methodologies.
Probability
Sampling Techniques
Probability sampling involves the
random selection of samples, ensuring that every individual in the population
has an equal chance of being chosen. This method enhances the
representativeness of the sample and reduces bias.
1.Simple Random Sampling
In simple random sampling, every
individual in the population is assigned a unique identifier, and samples are
selected using random mechanisms such as lottery or random number generators.
Example:
Selecting 50 students randomly from a university enrolment list.
2.Systematic Sampling
In this method, samples are
selected at regular intervals from an ordered population. For instance,
selecting every 10th individual from a list of 1,000 people.
3.Stratified Sampling
The population is divided into
homogeneous subgroups (strata), and samples are taken from each stratum
proportionally. This technique is useful when the population has distinct
subcategories.
Example:
Dividing a population by income levels and sampling within each group.
4.Cluster Sampling
Instead of sampling individuals,
entire clusters or groups are randomly selected. For example, choosing schools
randomly and then surveying all students within selected schools.
Non-Probability
Sampling Techniques
Non-probability sampling does not
involve random selection, and the samples are chosen based on the researcher’s
judgment or convenience. While this approach may introduce bias, it is often
practical and cost-effective.
Convenience Sampling
Samples are chosen based on
availability and ease of access. For example, surveying people at a mall.
Purposive Sampling
Researchers select participants based on specific characteristics or
criteria relevant to the study. For
example, selecting only experienced teachers for a study on teaching methods.
Quota Sampling
A specific quota is set for
different subgroups, and samples are chosen until the quota is met. For
instance, surveying 50 men and 50 women for gender-based analysis.
Snowball Sampling
Participants recruit others from
their network, making it useful for studying hard-to-reach populations.
Example:
Researching social behaviors among underground artists.
Table
1
Comparing
Probability and Non-Probability Sampling
|
Aspect |
Probability
Sampling |
Non-Probability
Sampling |
|
Basis
of Selection |
Random
selection |
Non-random
selection |
|
Bias |
Minimizes
bias |
May
involve bias |
|
Representativeness |
High |
Variable |
|
Cost
and Time |
Often
expensive and time-consuming |
Cost-effective
and quicker |
|
Applicability |
Suitable
for large-scale quantitative research |
Common
in qualitative and exploratory research |
Conclusion
The choice of sampling technique
depends on the research objectives, resources, and the nature of the population
under study. Probability sampling is preferred for generalizing results, while
non-probability sampling is suitable for exploratory or specialized research
contexts.
References
Babbie, E. R. (2020). The
Practice of Social Research. Cengage Learning.
Bryman, A. (2016). Social
Research Methods. Oxford University Press.
Creswell, J. W. (2014).
Research Design: Qualitative, Quantitative, and Mixed Methods Approaches.
SAGE Publications.
Flick, U. (2018). An
Introduction to Qualitative Research. SAGE Publications.
Kothari, C. R. (2004). Research
Methodology: Methods and Techniques. New Age International.
Neuman, W. L. (2014). Social
Research Methods: Qualitative and Quantitative Approaches. Pearson.
Patton, M. Q. (2015). Qualitative
Research & Evaluation Methods. SAGE Publications.
Teddlie, C., &
Tashakkori, A. (2009). Foundations of Mixed Methods Research. SAGE
Publications.
Yin, R. K. (2018). Case
Study Research and Applications: Design and Methods. SAGE Publications.
Zikmund, W. G. (2003). Business
Research Methods. South-Western.
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