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1. Unit II
Sampling Design- Census & Sample
Surveys; Steps in Sampling Design;
Types of Sample designs-Probability &
Non Probability sampling.

2. Population or Universe: It refers to the
group of people, items or units under
investigation and includes every individual.
Sample: a collection consisting of a part or
subset of the objects or individuals of population
which is selected for the purpose, representing the
population
Sampling: It is the process of selecting a sample
from the population. For this population is divided
into a number of parts called Sampling Units.

4. Samplingis the processof selectingobservations (a
sample) to provide anadequate description and
inferences of thepopulation.
Sample
It is aunit that is selected from
population
Represents the whole population
Purpose to draw theinference
WhySample???
Sampling Frame
Listing of population from which asample ischosen

5. Population
Sample
Samplin
g
Frame
Samplin
g
Process
What you
want to
talk about
What
you
actually
observe
in the
data
Inference

9. WHEN DATA IS TO BE COLLECTED FROM
EACH MEMBER OF THE POPULATION, IT
IS KNOWN AS CENSUS SURVEY
WHEN DATA IS TO BE COLLECTED ONLY
FROM SOME MEMBERS OF THE
POPULATION, IT IS KNOWN AS SAMPLE
SURVEY

10. Sampling Method Advantage over Census Method
 Speed : Less Time
 Economy : Less Expensive
 Adaptability
 Scientific Approach : More Dependable, Less Manpower, Less
Administrative Control
Census Method Advantage over Sampling Method
 Gives Exact & Accurate results

11. Sampling used in infinite cases while Census can’t
measure or studied
Ex : Inspection of Bombs
Test on Quality of Apples In those Census
Destroyed all itself
Census were Complete Enumeration while Sampling
were Partial Enumeration

12. Large population can be conveniently
covered.
Time, money and energy is saved.
Helpful when units of area are
homogenous.
Used when percent accuracy is not
acquired.
Used when the data is unlimited.

13. A true representative of the population.
Free from error due to bias.
Adequate in size for being reliable.
Units of sample should be independent and
relevant
Units of sample should be complete precise
and up to date
Free from random sampling error
Avoiding substituting the original sample for
convenience.

16. While developing a sampling design, the researcher must pay attention
to the following points:
a. Type of universe: The first step in developing a sampling design is to
clearly identify the universe to be studied. The universe can be finite
or infinite. In finite universe the number of items is certain,
for example number of workers in a factory, but in case of an infinite
universe we do not know the total number of items, for example
listeners of a radio programmed..

17. b. Sampling unit:
A decision has to be taken concerning a sampling
unit before selecting sample. Sampling unit may
be a geographical one such as state, district,
village, etc., or a social unit such as family,
individual, school, etc. The researcher will have
to decide one or more of such units that he has
to select for this study

18. c. Source list: It is also known as sampling frame from which sample is to
be drawn. It contains the names of all items of a universe. If source list is
not available, researcher has to prepare it. The list should be
comprehensive, reliable and appropriate. It is important to be as
representative of the population as possible.
d. Size of sample: This refers to the number of items to be selected from
the universe to constitute a sample. Choosing the number is a major
challenge before a researcher. The size of sample should neither be large,
nor too small. The number should be optimum. While deciding the size of
sample, researchers must determine the desired precision as also an
acceptable confidence level for the estimate. The indicators of interest in a
research study must be kept in view, while deciding the size of the sample.
Also, the costs factor also kept in mind while choosing the size of sample.

19. e. Indicators to study: In determining the sample design, one must
consider the question of the specific population parameters which
are of interest. For instance, you may be interested in estimating
the proportion of persons with some characteristic in the population,
or you may be interested in knowing some average or the other
measure concerning the population. There may also be important
sub-groups in the population about whom you would like to make
estimates.
f. Financial constraints: Cost considerations, from practical point of
view, have a major impact upon decisions relating to not only the
size of the sample but also to the type of sample.

21. All subsets of the frame are given an equal
probability.
Random number generators

22. Advantages
Minimal knowledge of
population needed
Easyto analyze data
Disadvantages:
Low frequency of use
Doesnot useresearchers’expertise
Largerrisk of randomerror

23. Population is divided into two or more groups
called strata
Subsamples are randomly selected from each
strata

24. Advantages:
Assuresrepresentation of all groups in
sample population
Characteristics of each stratum canbe
estimated and comparisons made
Disadvantages:
Requires accurate information on
proportions of eachstratum
Stratified lists costly to prepare

25. Thepopulation is divided into subgroups (clusters) like
families.
Asimple random sample is taken from eachcluster

26. Advantages:
Canestimate characteristics of both cluster
and population
Disadvantages:
Thecost to reach an element to sample is
very high
Eachstage in cluster sampling introduces
sampling error—the more stagesthere
are, the more error there tends tobe

27. Order all units in the samplingframe
Then every nth number on the list isselected
N=Sampling Interval

28. Advantages:
Moderate cost; moderate usage
Simple to drawsample
Easyto verify
Disadvantages:
Periodic ordering required

30. Theprobability of each casebeing selected from the
total population is not known.
Units of the sample are chosen on the basisof
personal judgment or convenience.
There are NOstatistical techniques for measuring
random sampling error in anon-probability sample.

31. A. Convenience Sampling
B.Quota Sampling
C.Judgmental Sampling (Purposive Sampling)
D.Snowball sampling
E.Self-selection sampling

32. Convenience sampling involves choosing respondents
at the convenience of theresearcher.
Advantages
Very low cost
Extensively used/understood
Disadvantages
Variability and bias cannot be measured or controlled
Projecting data beyond sample not justified
Restriction of Generalization.

33. Thepopulation is first segmented into mutually
exclusive sub-groups, just asin stratified sampling.
Advantages
Usedwhen research budget is limited
Very extensively used/understood
No need for list of populationelements
Disadvantages
Variability and bias cannot be measured/controlled
Time Consuming
Projecting data beyond sample not justified

34. Researcheremploys his or her own "expert”
judgment about.
Advantages
There is aassuranceof Quality response
Meet the specificobjective.
Disadvantages
Biasselection of sample mayoccur
Time consuming process.

35. Theresearch starts with akeyperson and
introduce the next one to becomeachain
Advantages
Low cost
Useful in specific circumstances & for locating rare
populations
Disadvantages
Not independent
Projecting data beyond sample not justified

36. It occurs when you allow each caseusually
individuals, to identify their desire to take part in the
research.
Advantages
More accurate
Useful in specific circumstances to serve thepurpose.
Disadvantages
More costly due toAdvertizing
Massare left

38. SAMPLING ERRORS

39. What is a sampling error?
A sampling error occurs when the
used in the study does not represent
entire population.
Sampling is a type of analysis where a
small sample of observations is chosen
from a larger population.

40. Types of common sampling error

41. •Population specification error
•A population specification error occurs when researchers don’t know
precisely who to survey.
For example, imagine a research study about kid’s apparel. Who is the
right person to survey? It can be both parents, only the mother, or the
child. The parents make purchase decisions, but the kids may influence
their choice.
•Sample frame error
•Sampling frame error occurs when researchers target the sub-
population wrongly while selecting the sample.
For example, picking a sampling frame from the telephone white pages
book may have erroneous inclusions because people shift their cities.
Erroneous exclusions occur when people prefer to un-list their

42. •Selection error
•Selection error occurs when respondents self-select themselves to
participate in the study. You can control selection errors by going the
extra step to request responses from the entire sample. Only interested
ones respond.
Pre-survey planning, follow-ups, and a neat and clean survey design will
boost respondents’ participation rate.
•Sampling errors
•Sampling errors occur due to a disparity in the representativeness of
the respondents. It majorly happens when the researcher does not plan
his sample carefully.
These sampling errors can be controlled and eliminated by creating a
careful sample design, having a large enough sample to reflect the
entire population, or using an online sample or survey audiences to

43. Non-sampling errors refers to biasesand
mistakes in selection of sample.
CAUSES FOR NON-SAMPLING
ERRORS
 Sampling operations
 Inadequate of response
 Misunderstanding the concept
 Lackof knowledge
 Concealment of the truth.
 Loaded questions
 Processing errors

44. What are the steps to reduce sampling errors?