non probability sampling methods gaaniko

1. NON PROBABABILITY SAMPLING METHODS.
Non-probability sampling is a sampling technique where the samples are gathered in a process
that does not give all the individuals in the population equal chances of being selected. It does
not follow the theory of probability in the choice of elements from the sampling population. Non
probability sampling is used when the number of elements in a population is either unknown or
cannot be individually identified. In such situations the selection of elements depends upon the
other considerations. There are four common non probabilities sampling techniques which are
both qualitative and quantitative research and these are:
1. Quota sampling
2. Accidental sampling
3. Judgment sampling or purposive sampling
4. Snowball sampling.
Example: We visit every household in a given street, and interview the first person to answer the
door. In any household with more than one occupant, this is a non-probability sample, because
some people are more likely to answer the door (e.g. an unemployed person who spends most of
their time at home is more likely to answer than an employed housemate who might be at work
when the interviewer calls) and it's not practical to calculate these probabilities.
1. Quota sampling
Quota sampling is a non-probability sampling technique where in the researcher ensures equal or
proportionate representation of subjects depending on which trait is considered as basis of the
quota.
For example, if basis of the quota is college year level and the researcher needs equal
representation, with a sample size of 100, he must select 25 1st year students, another 25 2nd
year students, 25 3rd year and 25 4th year students. The bases of the quota are usually age,
gender, education, race, religion and socioeconomic status

2. Main arguments for: quota sampling
1 Quota sampling is less costly. A quota interview on average costs only half or a third as much
as a random interview, but we must remember that precision is lost.
2 It is easy administratively. The labor of random selection is avoided, and so are the headaches
of non-contact and callbacks.
3 If fieldwork has to be done quickly, perhaps to reduce memory errors, quota sampling may be
the only possibility, e.g. to obtain immediate public reaction to some event.
4. Quota sampling is independent of the existence of sampling frames.
Main arguments against: Quota sampling
1. It is not possible to estimate sampling errors with quota sampling because of the absence of
randomness.
Some people argue that sampling errors are so small compared with all the other errors and
biases that enter into a survey that not being able to estimate is no great disadvantage. One does
not have the security, though, of being able to measure and control these errors.
2. The interviewer may fail to secure a representative sample of respondents in quota sampling.
For example, are those in the over 65 age group spread over all the age range or clustered around
65 and 66?
3. Social class controls leave a lot to the interviewer's judgment.
4. Sample selection may be biased, since statistical inferences cannot be made from the sample
to the population.
Purposive sampling.
The primary consideration in purposive sampling in your judgment as to who can provide the
best information to achieve the objectives of your study. The researcher only goes to those
people who in your opinion are likely to have the required information and be willing to share it

3. with you. This is used primarily when there are a limited number of people that have expertise in
the area being researched.
In a study where in a researcher wants to know what it takes to graduate at H.I.T, the only people
who can give the researcher first hand advise are the individuals who graduated hit. With this
very specific and very limited pool of individuals that can be considered as a subject. This
strategy is extremely useful when you want to describe the phenomenon that has a few being
known.
Strengths of purposive sampling.
1. Wide range of techniques. One of the key benefits of this sampling method is the ability to
gather large amounts of information by using a range of different techniques. Like critical
method, expert methods.
2. Ensures balance of group sizes when multiple groups are to be selected.
Weakness.
1. Research bias, as each sample is based entirely on the judgment of the researcher in question.
2. Difficult to defend populations due to potential subjectivity of researcher.
Snowball sampling
It is a sampling technique where you begin by identifying someone who meets the criteria for
inclusion in your study, then ask them to recommend others who they may know who also meet
the criteria. This method would hardly lead to representative samples, it may be the best method
available when dealing with population that is inaccessible or hard to find.
For example if are carrying out research on reasons for prostitution activities in Zimbabwe, you
begin by identifying one who later leads you to the others.
Advantages:
 It allows for studies to take place where otherwise it might be impossible to conduct
because of a lack of participants.

4.  Snowball sampling may help you discover characteristics about a population that you
weren’t aware existed. For example, the casual illegal downloader vs. the for-profit
downloader.
Disadvantages:
 It is usually impossible to determine the sampling error or make inferences about
populations based on the obtained sample.
 Snowball sampling is also known as cold-calling, chain sampling, chain-referral
sampling, and referral sampling.
Convenience sampling
This is sometimes known as grab or opportunity sampling or accidental or haphazard sampling.
With convenience sampling, the samples are selected because they are accessible to the
researcher. Subjects are chosen simply because they are easy to recruit. This technique is
considered easiest, cheapest and least time consuming.
For example, if the interviewer was to conduct a survey at join shopping center early in the
morning on a given day, the people that he/she could interview would be limited to those given
there at that given time, which would not represent the views of other members of society in such
an area, if the survey was to be conducted at different times of day and several times per week.
This type of sampling is most useful for pilot testing.
Strengths of convenience sampling
 saves time due to less exhaustive research on population
 Inexpensive way of ensuring sufficient numbers of a study
Weakness
 Not possible to prove that the sample is representative of designated population
 It cannot be generalized into conclusions.