2.  A sample design is a definite plan for
obtaining a sample from a given population .
It refers to the technique or the procedure
the researcher would adopt in selecting
items for the sample . Sample design may as
well lay down the number of items to be
included in the sample, i.e. , the size of
sample.

3.  TYPE OF UNIVERSE – The universe can be
finite or infinite. In finite universe the
number of items are finite.
 SAMPLE UNIT- A decision has to be taken
concerning a sample unit before selecting
sample. Sampling unit may be a geographical
one such as state, district, village etc.

4. * SOURCE LIST- It is also known as sample
frame from which it is to be drawn . It
contain the number of items of a universe.
* SIZE OF SAMPLE- The size of sample should
neither be excessively large, nor to small. It
should be optimum.

5. *PARAMETER OF INTEREST – In determining
the sample design , one must consider the
question of the specific population
parameter which are of interest .
* SAMPLING PROCEDURE – The researcher
must be decide the type of sample he will
use, i.e. , must decide about the technique
to be used in selective items for sample.

6.  PROBABILITY SAMPLING
 NON PROBABILITY SAMPLING
* PROBABILITY SAMPLING-
1 – Each and every unit of the population as
the equal chance for selection as a sample
unit.
2 – Also called formal sampling or random
sampling .
3 – Probability sample allow us to estimate the
accuracy of the sample.

7.  SAMPLE RANDON SAMPLING – There are 2
type simple random sample : -
1 – WITH REPLACEMENT – Simple random
sample the unit once selected has the
chance for again selection.
2 – WITH OUT REPLACEMENT – Simple random
sample the unit one selected can not be
selected again.

8.  SYSTEMATIC RANDOM SAMPLE -
1 – Order or unit in the sample frame based on
some variables and then every Nnth number
on the list is selected.
2 – Gaps between elements are equal and
constant.
3 – N = SAMPLING INTERVAL

9.  STRATIFIED RANDOM SAMPLING – Population is
divided into 2 or more groups called strata
according to some criteria such as -
geographical location , great level , age and
income and sub samples are randomly
selected from each strata . Elements with in
each strata are homogeneous but are
heterogeneous across strata.

10.  CLUSTER SAMPLING – The population is
divided into sub groups like families a simple
random sample is taken to the sub groups
and then all members of the cluster selected
are survey.

11.  NON PROBABILITY SAMPLING – The
probability of each case being selected from
the total population is not known units of the
sample are chosen on the basis of personal
judgment or convenience there are no
statical technique for measuring random
sampling error in a non probability sample .
 There are many point which are following as
:-

12.  1 – Involve non random method in selection
of sample .
 2 – All have not equal chance of being
selected .
 3 – selection depend upon situation .
 4 – considerably less expensive .

13.  QUOTA SAMPLING –
1 – The population is divided into cells on the
basis of relevant control characteristics .
2 – A quota of sample units is established for
each cell .
3 – A convenience sample is drawn for each cell
until the quota is met .
4 – It is entirely non random and it is normally
use for interview surveys .

14. * JUDGEMENTAL SAMPLING – In judgmental
sampling the judgment or opinion of same
experts from the basis of sample method it
is expected this samples would be suppose
to know the population .

15.  CONVENIENCE SAMPLING – In this , the
researcher according to his convenience
selects various sampling units . Often those
elements are selected in the sample , which
happen to be in right place and at right time
. Example of convenience sampling include :
-
 1 – Use of students or members of some
social organization research .
 2 – Test out questionnaire in magazine and
news paper .