non random sampling (final)
TRANSCRIPT
8/7/2019 Non Random sampling (Final)
http://slidepdf.com/reader/full/non-random-sampling-final 1/22
NON-RANDOM SAMPLING
8/7/2019 Non Random sampling (Final)
http://slidepdf.com/reader/full/non-random-sampling-final 2/22
Non Random Sampling Non Random sampling is method where The population
elements (Samples) are selected on the basis of Availability.
(People out of population volunteer themselves for the
research)
Some elements of the population have no chance of selection Or
where the probability of selection can not be accurately
determined.
It involves the selection of elements based on assumptions,
population of interest or selection criteria.
8/7/2019 Non Random sampling (Final)
http://slidepdf.com/reader/full/non-random-sampling-final 3/22
Example:
Interviewing 25 people with AIDS about there
experiences with HIV
could provide valuable insightsabout the stress and coping, rather than interviewing
people who do not suffer from AIDS Virus.
8/7/2019 Non Random sampling (Final)
http://slidepdf.com/reader/full/non-random-sampling-final 4/22
Non-random sampling is useful when descriptive
comments about the sample is desired.
Non-random sampling is biased sampling, as it is
certainly introduced.
The Samples are also selected on the researchers
personal judgment.
8/7/2019 Non Random sampling (Final)
http://slidepdf.com/reader/full/non-random-sampling-final 5/22
TYPES OF NON RANDOM SAMPLING
1. Convenience Sampling
2. Quota Sampling
3. Volunteer Sampling
4. Purposive Sampling
5. Snowball Sampling
8/7/2019 Non Random sampling (Final)
http://slidepdf.com/reader/full/non-random-sampling-final 6/22
Convenience Sampling Convenience sampling sometimes known as grab or
opportunity sampling.
It is a type of non random sampling which involves the sample
being drawn from the part of population which is easily
available.
A sample population selected because it is readily available andconvenient.
The researcher using such a sample cannot significantly make
generalizations about the total population from sample
because it would not be representative enough.
8/7/2019 Non Random sampling (Final)
http://slidepdf.com/reader/full/non-random-sampling-final 7/22
Example:
If the interviewer has to conduct such a survey at a
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 beconducted at different times of day and several times
per week.
8/7/2019 Non Random sampling (Final)
http://slidepdf.com/reader/full/non-random-sampling-final 8/22
Some more examples:-
the first ten cars to enter a car park
the first ten people to walk through a turnstile at a
sporting event, or
females in the first row of a concert.
8/7/2019 Non Random sampling (Final)
http://slidepdf.com/reader/full/non-random-sampling-final 9/22
8/7/2019 Non Random sampling (Final)
http://slidepdf.com/reader/full/non-random-sampling-final 10/22
Example:
Out of population of 5500 Men and 4500 Women,
quota samples or 100 individual ensure that 55 men
and 45 women are selected. The researcher goes out
the population and picks up people until the quotas
are filled up.
8/7/2019 Non Random sampling (Final)
http://slidepdf.com/reader/full/non-random-sampling-final 11/22
QUOTA V/S STRATIFIED SAMPLING
In Q uota Sampling, interviewer selects
first available subject who meets
criteria: is a convenience sample.
In Stratified Sampling, selection of
subject is random. Call-backs are used
to get that particular subject.
Highly controlled quota sampling uses
Probability sampling down to the last
block or telephone exchange
Stratified sampling without call-backs
may not, in practice, be much
different
fromQ uota sampling.
8/7/2019 Non Random sampling (Final)
http://slidepdf.com/reader/full/non-random-sampling-final 12/22
8/7/2019 Non Random sampling (Final)
http://slidepdf.com/reader/full/non-random-sampling-final 13/22
Example:
A television station may ask viewers to phone in to give their preferred
opinion on whether Australia should become a Republic. The station
would give two numbers to ring: one for Yes voters and the other forNo voters.
They would possibly give voters three hours to call after which the lines
would be closed and a conclusion formed. If 200 people called in, and
114 voted Yes and 86 voted No, then the television station would
report that 57% of callers voted Yes and 43% voted No. However, this
may or may not represent the opinion of the whole population.
However, the chance that the sample will be biased is very high because
only those with a telephone can vote, and only those watching television
or listening to radio at the time would be aware of the survey.
8/7/2019 Non Random sampling (Final)
http://slidepdf.com/reader/full/non-random-sampling-final 14/22
ADVANTAGE
The main advantages of phone-in sampling are that it is cheapin terms of time and money, and very easy to monitor and
control.
8/7/2019 Non Random sampling (Final)
http://slidepdf.com/reader/full/non-random-sampling-final 15/22
PURPOSIVE SAMPLING In this the researcher specifies the characteristics of the
population of interest and the locate/find the individuals who
match the characteristics.
Subjects selected for a good reason tied to purposes of
research
Small samples < 30, not large enough for power of probability
sampling
- Nature of research requires small sample
8/7/2019 Non Random sampling (Final)
http://slidepdf.com/reader/full/non-random-sampling-final 16/22
Example:
Market research firm decides to only include the boys
who are in 7th grade and have been diagnosed withH1N1 Virus. Then in this case the researcher will try
and find at least the 50 students who meet the
Inclusion criteria.
Some More Examples:-
Overweight children, First time mothers etc.
8/7/2019 Non Random sampling (Final)
http://slidepdf.com/reader/full/non-random-sampling-final 17/22
8/7/2019 Non Random sampling (Final)
http://slidepdf.com/reader/full/non-random-sampling-final 18/22
Example:
Study of the group of people who have power in the
area of educational policy making,In addition to thealready known positions of power like school board,
school superintendent, collage board etc.
8/7/2019 Non Random sampling (Final)
http://slidepdf.com/reader/full/non-random-sampling-final 19/22
Initi al Sample-2 F inal Sample-9
8/7/2019 Non Random sampling (Final)
http://slidepdf.com/reader/full/non-random-sampling-final 20/22
PROBLEMS WITH NON RANDOM SAMPLING
The problem with non-random samples is that there exist no
convincing method to generalize to the population.
Legitimate uses can include: controlled experiments, testing
questionnaires, exploring theoretical issues.
It may also be true (and it is often claimed) that changes can bemonitored adequately in volunteer samples. This is dubious.
8/7/2019 Non Random sampling (Final)
http://slidepdf.com/reader/full/non-random-sampling-final 21/22
CONTD..
Most users do not understand the legitimate uses and non uses
of non-probability samples. In particular we see a lot of over-interpretation of volunteer samples.
Another common misunderstanding is that users do not take
into account that non-probability samples (including purposive
samples) are still subject to random sampling error.
8/7/2019 Non Random sampling (Final)
http://slidepdf.com/reader/full/non-random-sampling-final 22/22
PGD
M Evening,2009-2012PRESENTED BY:
Abhishek Kumar(13/2009)
Chaitansi Sharma(16/2009)
Abhishek Kohli(17/2009)