CENSUS AND SAMPLE METHODS OF DATA COLLECTION- CLASS XI

2. What are we going to study in this chap
 Different techniques of data collection
i. Census method
ii. Sample method
 Types of sampling methods
 Sampling and non sampling errors

3. DEFINITION
•A survey which includes every element of the
population is known as census
or method of complete enumeration.
•Under this method , data is collected for each
And every unit of the investigation

4. The census of india is conducted
Every 10 years. It is available on
Various subjects : population,
Economy, finance,literacy, sex ratio etc.
Every five years , an agricultural
Census is conducted in india.
First such census was conducted
in 1970s

5. 1. Complete information can be obtained about
the whole population.
2. Data obtained from this method are more
reliable, accurate and representative.
3. In census method, no item is left out so,
the data is more adequate.
4. This method is quite useful when the field
of study is not big and intensive Survey is
to be made.
5. Data obtained from the complete
enumeration can be used in other
Investigations.

6. 1.It is more expensive and time consuming
method of data collection.
2.It is not applicable if population size is
infinite.
3.It contains errors due to non response,
biaseness of respondents.
4.Some errors or wrong information may
enter in an inquiry due to less Efficiency
of enumerator.

7. DEFINITION
•Sample method refers to
the process
Of learning about the
population on
The basis of sample drawn
from it.
•In sampling method,
instead of every
Item of the universe only a
part of the
Universe is studied and

9. 1. It is more economical because we do not h
to collect all data.
2. As no. Of units is only fraction of t
universe , Time
consumed Is also fraction of total time.
3. If sample is taken properly, the results
very reliable and
accurate.
4. This method is specially used for infin

10. 1. If the sample is not representative, the results will
not be correct. These will Lead to the wrong
conclusions.
2. Sometimes the universe is so small that the proper
samples cannot be taken.
3. It is a scientific method. Therefore, to get a good
and representative sample, one should have special
knowledge to get good sample and to perform proper
analysis so that reliable result may be achieved.
4. As in many cases the investigator, chooses samples,
such as convenience method, chances of personal bias
creep in.

11. Types of
sampling
methods
Probability
samples
Random
sampling
Systematic
sampling
Stratified
sampling
Cluster
sampling
Area
sampling
Non
probability
samples
Judgemental/
purposive
sampling
Convenience
sampling
Quota
sampling

12. Definition
A probability sampling scheme is one in which
every unit in the population has a chance(p>0) Of
being selected in the sample, and this probability
is known.
In this method, subset is selected on the basis
of some logic.
Example: if a researcher wants to select 10
students out of 70 students in a class, he can
choose them using any logic such as students

13. Simple random
sampling
Lottery method
Tippit’s random
tables

14. Definition
It is that method of sampling in which each and
every item of the
universe has an equal chance of being Selected.
In other words, there is an equal probability for
every item of the universe.
Example: LOTTERY METHOD
1. Each member of the population is assigned a
unique number or a code.
2. Then slips are prepared bearing those numbers.
3. They are placed in a box and shuffled properly
4.The investigator then picks up a slip randomly

15. Another method of random sampling is
Using the random number tables given
by Tippit, yates or fisher.
Tippit’s random no. Table consists of
10,400 four digited numbers, giving
in All 10,400*4= 41600 digits
selected at Random.
Suppose we have to select 2 out of
10 students in a class.
I. Assign no. To each student.
II. Now largest no. Is 10 which is two digit.
III. We can randomly select a spot to start
From.
IV. Suppose we start from 3rd no. In 1st column i.E;
2370. Now we will consider only first two digits. We can
move row wise or Column wise. As 23> 10 we’ll not consider
it.
V. Moving column wise and leaving the no. Greater than 10 ,
we can select 2 Numbers i.e; 5 & 10 .

16. Definition
According to this method, units of the population
are numerically, geographically, and alphabetically
arranged. Every nth item of the numbered items is
selected as a sample item.
Example : 10 out of 100 students selected at
random for this one can take 5th, 15th,….., 95th .
#Select any starting point and then select every
nth element of the population.

17. Definition
According to this method of sampling,
population is divided into different strata
having different characterstics and some
of the items are selected from each
strata, so that the Entire Population gets
represented.
male

18. Definition
In this technique, the total population is
divided into groups or clusters and a simple
random sample of the cluster is selected.
When sub divisions are meant to be
some geographical area, then cluster
sampling is known as area sampling.

19. DEFINITION
Non probability sampling is a technique
where the chances of any member being
selected for a sample cannot be calculated.
It is based on the subjective judgement of
the investigator.
Example: accidental or haphazard sampling

20. DEFINITION
•It is a sampling technique in which
researcher relies on his or her judgement
When choosing members of population to
participate in
the study .
•In this method, selection of the sample
items is not left out to the chance factors
but simply made by choice.
•It is also known as deliberate ,selective or

21. DEFINITION
It is a non probability
sampling technique
in which items are
selected on the
basis oftheir convenient
accessibility
and proximity to the
researcher.
It is also known as
availability sampling.

22. Definition
In this method, the population is divided into different groups according to different
characteristics of the population. Then, the investigators are simply given the quotas
to be filled from each group.
The size of the quotas is generally proportionate to the size of the group in the
population.
Example: a class XI has 100 students
Non medical - 20
Medical - 10
commerce - 30
arts - 40
Now there are 4 subgroups , an investigator selects a sample proportionately
Non medical - 4
Medical - 1
Commerce - 9
Arts - 16

23. Types of errors
Sampling
error
Non sampling
errors

24. BREAKING DOWN 'Sampling Error'
Sampling error can be eliminated when the sample
size is increased and also by ensuring that the sample
adequately represents the entire population.
A sampling error is a statistical error that occurs when an
investigator does not select a
sample that represents the entire population of data and the
results found in the
sample do not represent the results that would be obtained
from the entire population.
SAMPLING ERROR
Estimated value of parameter –true value of parameter

25. DEFINITION
Non-sampling errors can be defined as
errors arising during the
course of all survey activities other than
sampling. These are the errors related to
the collection of data.
These are of following types:
a) Error of measurement
b) Error of non response
c) Error of misinterpretation
d) Error of calculation or arithmetical errror

26. Why stratified sampling is known as
mixed sampling?
This method involves the mixture of
both purposive sampling and random
Sampling.The division of population
into different strata is purposely
done
while selection of the items is done
at random.