This document discusses various sampling methods and concepts. It defines key terms like target population, sampling unit, and sampling frame. It then describes different probability sampling techniques like simple random sampling, systematic sampling, and stratified sampling. It also covers non-probability sampling techniques like convenience sampling and judgment sampling. The document emphasizes selecting the most appropriate sampling design based on factors like accuracy needed, available resources, and knowledge of the population. It concludes with discussing internet sampling methods like using web site visitors, established panels, and opt-in lists.

1. Sampling Design and Sampling
Distributions
Presented By:
• Mudit Singla (51)
• Vikas Sonwane (53)
• Manisha Tripathy(55)
• Vaibhav Sood (57)
• Aayush Velaga (59)

2. Target Population
The target population is the collection of elements or
objects that possess the information sought by the
researcher and about which inferences are to be made.

3. Terminology
– An element is the object about which or from which the
information is desired, e.g., the respondent
– A sampling unit is an element, or a unit containing the
element, that is available for selection at some stage of
the sampling process
– Extent refers to the geographical boundaries
– Time is the time period under consideration

4. Important qualitative factors that
determine the sample size
– The importance of the
decision
– The nature of the
research
– The number of variables
– The nature of the
analysis
– Sample sizes used in
similar studies
– Incidence rates
– Completion rates
– Resource constraints

5. The
Sampling
Frame
Define the target population
Select a sampling frame
Conduct fieldwork
Determine if a probability or non-probability
sampling method will be chosen
Plan procedure
for selecting sampling units
Determine sample size
Select actual sampling units

6. Statistical Errors
The difference between the value of a sample
statistic of interest and the value of the
corresponding population parameter a statistical
error has occurred.

7. Types of Errors
Random Sampling Error
• The difference between the
sample result and the result
of a census conducted using
identical procedures
• These errors are due to
chance fluctuations
Systematic Error
• Systematic (non sampling)
errors result from non
sampling factors, primarily
the nature of a study’s
design and the correctness
of execution
• These are not due to chance
fluctuations

8. Illustration

9. Classification of Sampling
Techniques
Sampling Techniques
Nonprobability
Sampling Techniques
Probability
Sampling Techniques
Convenience
Sampling
Judgmental
Sampling
Quota
Sampling
Snowball
Sampling
Systematic
Sampling
Stratified
Sampling
Cluster
Sampling
Other Sampling
Techniques
Simple Random
Sampling

10. Types of Non probability sampling
Convenience
Sampling
Judgment
Sampling
Quota
Sampling
Snowball
sampling

11. • The sampling procedure of obtaining those
people or units that are most conveniently
available.
• Best used for exploratory research.
Convenience
Sampling

12. • A non probability sampling technique in which
an experienced individual selects the sample
based on personal judgment about some
appropriate characteristics of the sample
member
Judgment
Sampling

13. • A non probability sampling procedure that
ensures that various subgroups of a population
will be represented on pertinent characteristics
to the exact extent that the investigator desires.
• POSSIBLE SOURCES OF BIAS
– haphazard selection of subjects
• ADVANTAGES
– Speed of data collection
– Lower costs
– Convenience
Quota
Sampling

14. • A sampling procedure in which initial
respondents are selected by probability
methods and additional respondents are
obtained from information provided by the
initial respondents.
• It uses referrals for selecting respondents
• ADVANTAGES
– Reduced sample size
– Reduced cost
Snowball
sampling

15. Probability Sampling
The sampling techniques where selection
procedure is based on chance are called
probability sampling techniques.

16. Types of Probability Sampling
Simple Random
Sampling
Systematic
Sampling
Stratified Sampling
Proportional
versus
Disproportional
Sampling
Cluster Sampling
Multistage area
sampling

17. The sampling procedure
that ensures each element
in the population will have
an equal chance of being
included in the sample is
called simple random
sampling.
Simple Random
Sampling

18. A sampling procedure in which a starting point is
selected by a random process and then every
nth number on the list is selected.
Systematic
Sampling

19. A probability sampling procedure in which
simple random subsamples that are more or less
equal on some characteristic are drawn from
within each stratum of population.
Stratified
Sampling

20. Proportional
A stratified sample in which
the number of sampling units
drawn from each stratum is in
proportion to the population
size of that stratum.
Disproportional
A stratified sample in which
the sample size for each
stratum is allocated according
to analytical considerations
Proportional
versus
Disproportional
Sampling

21. An economically efficient
sampling technique in
which the primary
sampling unit is not the
individual element in the
population but a cluster of
element; clusters are
selected randomly.
Cluster
Sampling

22. Sampling that involves
using a combination of
two or more probability
sampling techniques
Multistage area
sampling

23. Selecting an Appropriate Sample
Design
A researcher who must decide on the most
appropriate sample design for a specific project will
identify a number of sampling criteria and evaluate
the relative importance of each criterion before
selecting a sampling design.

24. Sampling Criterion
• Degree of Accuracy – Depends on the researcher’s
tolerance for errors in sampling and requirements of the
project
• Resources – Depends on the researcher’s financial and
human resource constraints
• Time – Depends on the deadline of the project
completion
• Advance Knowledge of the Population – Depends on the
availability of details of population characteristics
• National vs Local – Depends on the geographic
proximity of the population elements

27. Internet Sampling
Advantages
• Allow researchers to reach a large sample rapidly
• Sample size requirements can be met quickly
• Easier to carry out
• Less costly
Disadvantages
• Lack of computer ownership and internet access
• Unrepresentative of all target populations

28. • Volunteer respondents
• Unrestricted/convenience samples
• Arrive haphazardly
• Random selection of sample units is a better option
• Done through Pop-up ads
• Problem of over representing the frequent visitors to the
site
• Can be controlled by several techniques like cookies,
prescreening etc
• Valuable if the target population is defined as visitors to a
particular Web site
Web Site Visitors

29. Panel Samples
• Drawing a probability sample from an established
consumer panel or other pre-recruited membership
panel
• Yields a high response rate
• Easier to select the panelists based on the data of their
previously answered questionnaires
• Panelists are compensated for their time with a
sweepstakes, a small cash incentive, or redeemable
points, etc
• Allows the company to draw simple random samples,
stratified samples, and quota samples

30. Recruited Ad Hoc Samples
• A sampling frame of e-mail addresses on an ad hoc basis
• Can be done online or offline
• Can be compiled from many sources, including
customer/client lists, advertising banners on pop-up
windows that recruit survey participants, online
sweepstakes, and registration forms
• Respondents maybe contacted by “snail mail” or by
telephone to ask for their e-mail addresses and obtain
permission for an Internet survey
• Offline techniques used are random-digit dialing and
short telephone screening interviews

31. Opt-in Lists
• To give permission to receive selected e-mail, such as
questionnaires, from a company with an internet
presence
• E-mail is sent only to authorized recipients
• Each individual has to confirm and reconfirm their
consent to participate in the survey
• Unsolicited survey request is treated as spam
• High response rate cannot be expected from the
individuals who have not agreed to be surveyed
• It can lead to complaints to the Internet Service Providers
and the survey site may be shut down