PROBABLE SAMPLING TYPES OF SAMPLING .ppt

Population:-
“Population is a group member possess specific attribute, that a researcher is interested in studying”.
Laura-A Talbot 1995
Sample:-
“A sample is a portion of population that has been selected to represent the population interest”.
Laura-A Talbot 1995
Sampling :-
“Sampling involves selecting a groups of people, events behaviors or other elements with which to Conduct a study. A Sampling plan defines the selection process and the sample defines the selected group of people (or elements) samples represent a population of people”.
Rose Marie 1998
“It is the process of selecting a portion of the population to represent the entire population”. Laura-A Talbot 1995
Sampling :-
“Sampling involves selecting a groups of people, events behaviors or other elements with which to Conduct a study. A Sampling plan defines the selection process and the sample defines the selected group of people (or elements) samples represent a population of people”.
Rose Marie 1998
“It is the process of selecting a portion of the population to represent the entire population”. Laura-A Talbot 1995
Probability sampling is one in which every unit of the population has equal probability of being selected for the sample .
It offers a high degree of representative.













Sampling is the selection of the group of person from a population with each person having an equal chance of being selected.
The objectives is to draw a representative sample and the result obtained from the sample can be generalized to the population.
Size of the universe must be known.
Desired sample size must be specific.
Each elements must have an eual chance of being selected.
Complete list of subject to be studied is available.
(I) Probability Samlping

Simple Random Sampling
Simple random sampling is a carefully controlled process.
The researcher:-
► Defines. The population (a set)
► Lists all of the units of the population (A sampling trams)
► Selects a sample of units (a subset) from which the samples are selected.
.
which is commonly used for selecting the prize winners in lottery here the selection is random or unpredictable and therefore fair the every item has an equal change to be selected

MERITS :-

There is no possibility of personal bias of the researcher in the selection of items. Probability theory can be used for generalization.

DEMERITS :-

It is time consuming and Expensive, If the items are not homogonous either in size or in nature. This method can not be applied.
Straified Random Sampling
In some cases, the population to be sampled is not homogenous but in essence, of several sub populations.
Eg :- The population of working women can be divided into higher income group, middle income group and lower income group based on their income.

MERITS :-
All the significant groups are represented units are concentrated and localized with in each stratum.
DEMERITS :-

1. PREPARED BY:
Mr. Abhinav Bhatt

2. Population:-
“Population is a group member possess
specific attribute, that a researcher is interested
in studying”.
Laura-A Talbot 1995
Sample:-
“A sample is a portion of population that
has been selected to represent the population
interest”.
Laura-A Talbot 1995

3. Sampling :-
“Sampling involves selecting a groups of
people, events behaviors or other elements with
which to Conduct a study. A Sampling plan
defines the selection process and the sample
defines the selected group of people (or
elements) samples represent a population of
people”.
Rose Marie 1998
 “It is the process of selecting a portion of
the population to represent the entire
population”. Laura-A
Talbot 1995

4. Sampling
Probability Sampling Non Probability Sampling
Simple Random
Stratified RandomSystematic Cluster
Accidental or IncidentalJudgmentalQuota ConvenienceSequentialSnow Ball
Multi phase

5. Probability sampling is one in which every unit
of the population has equal probability of being
selected for the sample .
It offers a high degree of representative.

6. Sampling is the selection of the group of
person from a population with each person
having an equal chance of being selected.
The objectives is to draw a representative
sample and the result obtained from the
sample can be generalized to the population.

7. Size of the universe must be known.
Desired sample size must be specific.
Each elements must have an eual chance of
being selected.
Complete list of subject to be studied is
available.

9. (I)Probability Samlping
Simple Random Sampling
Simple random sampling is a carefully
controlled process.
The researcher:-
► Defines. The population (a set)
► Lists all of the units of the population (A
sampling trams)
► Selects a sample of units (a subset) from
which the samples are selected.
.

10. which is commonly used for selecting the prize
winners in lottery here the selection is random or
unpredictable and therefore fair the every item has
an equal change to be selected

11. MERITS :-
There is no possibility of personal bias
of the researcher in the selection of items.
Probability theory can be used for generalization.
DEMERITS :-
It is time consuming and Expensive, If
the items are not homogonous either in size or in
nature. This method can not be applied.

12. Straified Random Sampling
In some cases, the population to be
sampled is not homogenous but in essence, of
several sub populations.
Eg :- The population of working
women can be divided into higher income group,
middle income group and lower income group
based on their income.
MERITS :-
All the significant groups are
represented units are concentrated and localized
with in each stratum.
DEMERITS :-
Bias may be caused in the sample
through improper stratification.

13. MERITS :-
All the significant groups are
represented units are concentrated and localized
with in each stratum.
DEMERITS :-
Bias may be caused in the sample
through improper stratification.

14. Systematic Sampling :-
This refers to sampling strategy that
involves the selection of subjects drown a
population list at fixed intervals the sampling
method interval refers standard distance
between the elements choose for sample.
Eg :- consider a population of about
100 peoples and the sample needed is 20 By
systemic sampling it can be calculated as,
Total population (N) 100
Sample size (k) = = 5
Sample population (n) 20
And it can calculated as 5th , 10th
….100th sample. So that can get 20 sample.

15. MERITS :-
Results are obtained in a convenient
and efficient manners.
Demerits :-
Bias in the form of non randomness .
E.g.:- If population list is arranged so that,
certain elements concedes with the sampling.

16. Cluster Sampling :-
Cluster sampling involves a successive
random sampling of units that progresses from
large to small.
E.g:- There is a successive random sampling of
units The first unit large groupings, or clusters, In
drawing a sample of nursing students, all might
first draw a random sample of nursing schools
and then draw a sample of students from the
selected schools. That usual procedure for
selecting sample such administrative units as
sates, cities and then house locks. Because of the
successive stages in caster sampling, this
approach is often called multistage sampling

17. Merits :-
More Economical in terms of time and money
than other types of probability sampling.
Demerits :-
More sampling errors tend to occur
The appropriate handling of the statistical dated
from cluster samples is very complex.

18. (5) Multiphase sampling:
In this method information is collected from the
whole sample and part of information is from sub
sample.
Eg: Tuberculosis survey
Here simple and cheep tests like montoux test was
done to all cases of sample first phase. Those who
are positive for montoux test are screened by x-ray
chest (or MMR) which is more expensive than the
first test – II phase.
Those who are positive for x-ray chest and clinical
symptoms, their sputum examination is done
(concrete technique) Three phase
So, those who need sputum examination will be
small.

19. MERIT:
Frequently use.
High cost.
More purposeful.
DEMERIT:
It is suitable when there is no unique variation in
the universe.
Depends on the techniques combined.

20. If the target population identified?
Is the accessible population identified?
was the probability (or) Non probability method?
Is the specific sampling method appropriate for
the stud
Is the sampling method technique described?
Are the demographic characteristics of the
sample presented?
..contd..

21. Are the demographic characteristics of the
sample presented?
Is the sample size adequate?
Is the sample representative the population?
Are potential sampling biases identified?
Is subject dropout discussed?