Non – Probability Sampling (Convenience, Purposive).

1. NON – PROBABILITY SAMPLING
(CONVENIENCE, PURPOSIVE).

2. Sampling is the act, process, or technique
of selecting a representative part of a
population for the purpose of determining
parameters or characteristics of the whole
population.
INTRODUCTION

3. Sampling is concerned with the selection
of a subset of individuals from population
to estimate characteristics of the whole
population.
Sampling is a process of collection of
data
Sampling is a good representative of the
population.
MEANING OF SAMPLING

4. W. G. Cocharn: “In every branch of science we lack the
resources, to study more than a fragment of the
phenomena that might advance our knowledge”. In this
definition, a ‘fragment’ is the sample and ‘phenomena’ is
the ‘population’. The sample observation are applied to
the phenomena, i.e. generation.
David S. Fox: “In the social sciences, it is not possible to
collect data from every respondent relevant to our study
but only from some fractional part of that respondents.
The process of selecting, the fractional, part is called
sampling. ‘Sampling design’ means the joint procedure of
selection and estimation. Sampling should be such that
error of estimation is minimum.
DEFINITION OF SAMPLING:

5. The sampling method was used in social sciences research
as early as in 1754 by A.L Bowley.
When the population is very large, it can be satisfactorily
covered through sampling.
It saves a lot of time energy and money.
Especially when the units of an area are homogeneous,
sampling techniques is really useful.
When the data are unlimited, the use of this method is really
useful.
When cent percent accuracy is not required, the use of this
technique becomes inevitable.
When the number of individuals to be studied is
manageable intensive study becomes possible.
IMPORTANT OF SAMPLING

6. Characteristics of a Good Sample
•True representative
•Free from bias
•Objective
•Accurate
•Comprehensive
•Economical
•Approachable.
•Good size
•Feasible
•Practical

7. ADVANTAGES OF SAMPLING
Reduced cost: It is economical.
Greater Speed: Sampling is less time consuming than the census technique.
Greater Scope: It has great scope and flexibility.
Greater Accuracy: Sampling ensure high degree of accuracy due to a limited
area of operation.
DISADVANTAGES OF SAMPLING
Less Accuracy: Conclusions derived from sampling are more liable to error.
Changeability of units:
Difficulties in selecting a truly representative sample: The results of a
sample are accurate and usable only when the sample is representative of the whole
group.
Need for specialized knowledge: Sampling method requires a specialised
knowledge in sampling technique statistical analysis and calculation of probable
error.

8. TECHNIQUES OF SAMPLING
•Probability sampling techniques.
•Non – probability sampling techniques.
Probability sampling techniques: Probability sampling
is a sampling technique wherein the samples are gathered
in a process that gives all the individuals in the population
equal chances of being selected.
According to G. C Halmstadter, “A probability sample is
one that has been selected in such a way that every element
chosen has a known probability of being included.

9. TECHNIQUES OF PROBABILITY
SAMPLING
Simple random sampling.
Systematic sampling.
Stratified sampling
Multiple or double sampling
Multistage Sampling
Cluster sampling.

10. NON – PROBABILITY SAMPLING
Non – probability sampling is a sampling
technique where the samples are gathered in
a process that does not all the individuals in
the population equal chances of being
selected.
In the absence of any idea of probability
the method of sampling is known as Non –
probability sampling.

11. Characteristics of Non – Probability Sampling
There is no idea of population.
There is no probability of selecting any individual.
In has free distribution.
The observations are not used for generalisation
purpose.
Non – parametric or non – inferential statistics are
used.
There is no risk for drawing conclusions.

12. Types of Non – Probability Sampling
oConvenience sampling
oPurposive sampling
oQuote sampling
oIncidental sampling
oSnowball sampling.

13. Convenience Sampling
This is also known as ‘accidental’ or
“haphazard” sampling
Sample is selected according to the convenience
of the sample.
No pre – planning is necessary for the selection
of items.
The convenience may be in respect of
availability of source list, accessibility of the units,
etc.

14. EXAMPLES OF CONVENIENCE SAMPLING
The researcher engaged in the study of university
students might visit the university canteen, library,
some departments, play ground, verandahs and
interview certain number of students.
Another example is of election study. During
election times, media personnel often present man
– on – the – street interviews that are presumed to
reflect public opinion. In this sampling
representativeness is not significant.

15. MERIT OF CONVENIENCE SAMPLING
Convenience sampling is quick and economical.
Convenience sampling are best utilised for
exploratory research when additional research with
subsequently be conducted with a probability
sample.
A convenience sampling may be used in any one or
more cases when the universes is not clearly defined.

16. DEMERIT OF CONVENIENCE SAMPLING
It is unscientific.
It is a biased sampling method.
Sampling unit is not clear.
A complete source list is not available.

17. PURPOSIVE SAMPLING
•This sampling method is also known as judgemental
sampling.
•Appropriate characteristic required of the sample
members.
•Sampling is possible only when there is a specific
objective.
•This method need not be used when there are multi
– purpose objectives involved in the study.
•The investigator has to pick up only such sample
which is relevant to his study.
• The investigator should possess full knowledge of
the universe.

18. EXAMPLES OF PURPOSIVE SAMPLING
Suppose, the researcher wants to study beggars.
He knows the three areas in the city where the
beggars are found in abundance. He will visit only
these three areas and interview beggars of his
choice and convenience.
Popular journals conduct surveys in selected
metropolitan cities to assess the popularity of
politicians and political parties or to forecast
election results.

19. MERITS OF PURPOSIVE SAMPLING
It uses the best available knowledge
concerning the sample subjects.
It give better control of significant
variables.
In it sample group data can be easily
matched.
In it there is homogeneity of subject used
in the sample.

20. DEMERITS OF PURPOSIVE SAMPLING
In it the reliability of the criterion is questionable.
In it the knowledge of population is essential.
In is there may be errors in classifying sampling
subjects.
It is unable to utilise the inferential parametric
statistics.
It is unable to make generalization convening total
population.

21. CONCLUSION
On the basis of sample study, we can predict
and generalise the behaviour of the
population.
Most researchers come to a conclusion of
their study by studying a small sample from the
huge population or universe.