Non Probablity Sampling for research methods

DR. RAJANI KUMAR
Non Probablity Sampling

• Measuring a small portion of
something and then making a
general statement about the whole
thing.
• Process of selecting a number of
units for a study in such a way that
the units represent the larger group
from which they are selected
Sampling

• Sampling makes possible the study of a large,
(different characteristics) population.
• Sampling is for economy
• Sampling is for speed.
• Sampling is for accuracy.
• Sampling saves the sources of data
from being all consumed
Why We Need Sampling?

1.Probability sampling
2. Non-probability sampling
General Types of Sampling

• Unequal chance of being included in the sample
(non-random)
• Samples are selected for a specific purpose with a
pre determined basis of selection.
• The sample is not a proportion of the population and
there is no system in selecting the sample. The
selection depends upon the situation.
• No assurance is given that each item has a chance
of being included as a sample
• There is an assumption that there is an even
distribution of characteristics within the population,
believing that any sample would be representative
Non-probability sampling

• Judgment or purposive or deliberate
sampling
• Convenience sampling
• Quota sampling
• Snow Ball Sampling
Types of Non-Probability Sampling

In this method of sampling the choice of sample
items depends primarily on the judgment of the
researcher. In other words, the researcher
determines and includes those items in the
sample which he thinks are most typical of the
universe with regard to the characteristics of
research project.
Judgment or purposive or deliberate
sampling

Non Probablity Sampling for research methods

• If there are a small number of sampling units is in
the universe, judgment sampling enables
inclusion of important units.
• Judgment stratification of population helps in
obtaining a more representative sample in case
research study wants to look into unknown traits
of the population.
• Judgment sampling is a practical method to
arrive at some solution to everyday business
problems.
The use of judgment sampling is
justified by following premises:

Limitations:
• The judgment sampling involves the risk that
the researcher may establish conclusions by
including those items in the sample which
conform to his preconceived ideas.
• There is no objective way of evaluating the
reliability of sample results.

2. Convenience sampling
• Convenience sampling is commonly known as
unsystematic, accidental or opportunistic sampling.
• According to this procedure a sample is selected according
to the convenience of the investigator.
• In this method of sampling the choice of sample items
depends primarily on the judgment of the researcher. In
other words, the researcher determines and includes those
items in the sample which he thinks are most typical of the
universe with regard to the characteristics of research
project.
• A type of non probability sampling which involves the
sample being drawn from that part of the population which
is close to hand. That is, readily available and convenient.
• For example, suppose 100 car owners are to be selected. Then we may
collect from the RTO's office the list of car owners and then make a selection
of 100 from that to form the sample.

3. QUOTA SAMPLING
• In this method, the sample size is determined first and
then quota is fixed for various categories of
population, which is followed while selecting the
sample.
• The quota has to be determined in advance and
intimated to the investigator. The quota for each
segment of the population may be fixed at random or
with a specific basis. Normally such a sampling
method does not ensure representativeness of the
population.
• Example: - Suppose we want to select 100 students, then we might say
that the sample should be according to the quota given below : Boys 50%,
Girls 50% Then among the boys, 20% college students, 40% plus two
students, 30% high school students and 10% elementary school students. A
different or the same quota may be fixed for the girls.

Reduces cost of preparing sample and field work, since
ultimate units can be selected so that they are close
together.
Introduces some stratification effect.
DEMERITS OF QUOTA SAMPLING
• Introduces bias
• Since random sampling is not involved at any stage, the
errors of the method cannot be estimated by statistical
procedures.
• Quota sampling is most commonly used in marketing
survey and Election Poll
MERITS OF QUOTA SAMPLING

• It refers to Identifying someone who meets
the criteria for inclusion in the study.
• Selection of additional respondents is
based on referrals from the initial
respondents
4. SNOWBALL SAMPLING

1. Linear Snowball Sampling: The formation of a sample starts with one individual
subject providing information about just one other subject and then the chain
continues with only one referral from one subject. This pattern is continued until
enough number of subjects are available for the sample.
2. Exponential Non-Discriminative Snowball Sampling: In this type, the first
subject is recruited and then he/she provides multiple referrals. Each new referral
then provides with more data for referral and so on, until there is enough number
of subjects for the sample.
3. Exponential Discriminative Snowball Sampling: In this technique, each
subject gives multiple referrals, however, only one subject is recruited from each
referral. The choice of a new subject depends on the nature of the research
study.
Types of Snowball Sampling

It’s quicker to find samples: Referrals make it easy and quick to find
subjects as they come from reliable sources. An additional task is saved
for a researcher, this time can be used in conducting the study.
Cost effective: This method is cost effective as the referrals are obtained
from a primary data source. It’s is convenient and not so expensive as
compared to other methods.
Sample hesitant subjects: Some people do not want to come forward
and participate in research studies, because they don’t want their identity
to be exposed.
Advantages of Snowball Sampling

Non Probablity Sampling for research methods

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