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overall student population (e.g., 20% law, 30% science, 50% arts).

Step 2: Selecting the sample - The researcher starts selecting
◆ Selecting the sample
participants within each quota category. They may approach
students on campus and ask questions to determine their age and
discipline. Once they find a student who meets the criteria of a
specific quota category (e.g., a 20-year-old law student), they
include that student in the sample. The researcher continues this
process until they have reached the predetermined quotas for each
◆ Adjustments category.
Step 3: Adjustments - In quota sampling, if a particular quota
category is filled before completing the sample, the researcher
might move on to the next category or adjust the selection process
to include other participants while still maintaining the overall
quotas.
In this example, the researcher would continue to collect
◆ Sampling based on
quotas data until the desired number of participants from each age and
discipline category is reached. The final sample will mirror the
proportions of the entire student population with respect to age
and discipline. It is important to note that quota sampling does
not involve random selection and, therefore, does not guarantee
a fully representative sample. However, it can be a practical and
cost-effective approach when conducting surveys or research
studies with specific constraints.
D. Snowball sampling
This method collects samples in a fashion as to how a ball
rolls, so is a fancy name being given to the sampling technique.
◆ Generate lead A few respondents are initially selected and they provide the lead
from few initial
respondents to other respondents, say for e.g. if the researcher wants to study
about the students who opt to study abroad after their graduation,
one or two can be initially selected and they would provide names
of similar students. The process continues like a snowball rolling
downhill, growing in size as more participants are added. This
method is often used when the target population is difficult to
reach or locate. It is particularly useful for studying rare or hidden
populations. There is no probability of all elements being included
being the major disadvantage of the method.

Criteria for selecting an appropriate sampling technique
◆ Problem i. Nature of the problem- It involves the specific question the
characteristic
researchers want to study. The choice of sampling technique
depends on the nature of the problem. For instance, if the problem
requires gathering data from a small population were population
list if available, a simple random sampling technique may be more
suitable. Whereas if the problem requires a representative sample
from various subgroups, a stratified sampling technique might be

62 SGOU - SLM -MCom Research Methodology