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Malar Kodi S
Assistant Professor
College of Nursing
AIIMS Rishikesh
Outlines
 Sample definition
 Purpose of sampling
 Process in the selection of a sample
 Types of sampling
 Non probability sampling technique
Sampling is the process of selecting
observations (a sample) to provide an
adequate description and inferences of the
population.
What is Sampling?
Sampling is the act, process or technique of selecting a
suitable sample or a representative part of a population
for the purpose of determining parameters or
characteristics of the whole population
Suitable sample
Why Sampling instead of doing
a census?
Economy
Timeliness
Large size of population
Inaccessibility of some
population
Destructiveness of the
observation
Accuracy
POPULATION
The Theoretically specified
Aggregation of study elements.
Population
Sample
Sampling
Frame
Sampling
Process
What you
want to
talk about
What you
actually
observe
in the
data
Inference
Sampling criteria
Inclusion criteria- The criteria that specify population
characteristics
Exclusion Criteria- A population is defined in terms
of characteristics that people must
not possess
CONCEPTS OF SAMPLING
Target population
The aggregate of cases about which
Researcher would like to generalize
Whom do you wish to
generalize the findings?
Accessible population
The aggregate of cases conform
to designated criteria and that
are accessible
Which Population do
You have access?
Sampling Frame
The List or procedure defining the
Population (from which the sample
will be drawn)
E.g Telephone book ,Voters list
Through what resource
you can access them?
Sample
Subset of population elements
Who is participating
in your Study?
Probability
samples
Non-
probability
samples
 All subsets of the frame are given an
equal probability.
 Random number generators
Advantages:
 Minimal knowledge of population
needed
 Easy to analyze data
Disadvantages:
 Low frequency of use
 Does not use researchers’ expertise
 Larger risk of random error
 Population is divided into two or more
groups called strata
 Subsamples are randomly selected from each
strata
Advantages:
 Assures representation of all groups
in sample population
 Characteristics of each stratum can be
estimated and comparisons made
Disadvantages:
 Requires accurate information on
proportions of each stratum
 Stratified lists costly to prepare
 The population is divided into subgroups (clusters) like
families.
 A simple random sample is taken from each cluster
Advantages:
Can estimate characteristics of both cluster
and population
Disadvantages:
The cost to reach an element to sample is
very high
Each stage in cluster sampling introduces
sampling error—the more stages there are,
the more error there tends to be
 Order all units in the sampling frame
 Then every nth number on the list is selected
 N= Sampling Interval
Advantages:
 Moderate cost; moderate usage
 Simple to draw sample
 Easy to verify
Disadvantages:
 Periodic ordering required
 Carried out in stages
 Using smaller and smaller sampling units at each
stage
 Most commonly used sampling design in practice
 Involves more than one stage of sampling and/or a
combination of two or more sampling designs
Advantages:
 More Accurate
 More Effective
Disadvantages:
 Costly
 Each stage in sampling introduces sampling
error—the more stages there are, the
more error there tends to be
 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 statistical techniques for measuring
random sampling error in a non-probability sample.
Non
probability
sampling
technique
Convenience
Sampling
Quota
Sampling
Judgmental
Sampling
(Purposive
Sampling)
Snowball
sampling
Self
selecting
Sampling
Consecutive
sampling
 Convenience sampling involves choosing
respondents
at the convenience of the researcher
.
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.
• The population is first segmented into mutually exclusive sub-
groups, just as in stratified sampling.
• Judgment Used To Select Subjects From Each Segment
Advantages
 Used when research budget is
limited
 Very extensively
used/understood
 No need for list of population
elements
Disadvantages
 Variability and bias cannot be
measured/controlled
 Time Consuming
 Projecting data beyond sample
not justified
 Researcher employs his or her own "expert”judgment
about.
 Subjects are selected purposely who are judged to be
typical population and knowledgeable about the
issues
under the study
E.g. Home care of Diabetes mellitus, case studies
Advantages
 There is a assurance of Quality
response
 Meet the specific objective.
Disadvantages
 Bias selection of sample may
occur
 Time consuming process.
 The research starts with a key person and introduce
the next one to become a chain Network or Chain
sampling
Advantages
 Low cost
 Useful in specific
circumstances & for locating
rare populations
Disadvantages
 Not independent
 Projecting data beyond sample
not justified
 It occurs when you allow each case usually
individuals, to identify their desire to take part in the
research.
 Select who volunteer for the sample
Advantages
 More accurate
 Useful in specific circumstances
to serve the purpose.
Disadvantages
 More costly due to Advertizing
 Mass are left
Consecutive sampling
Sampling Error
o The Fluctuation of the value of a statistics from
one sample to another drawn from the same population
o The systematic over- representation or under
representation of some segment of the population
in terms of a characteristic relevant to the
research question
 Specific problem selection.
 Systematic documentation of related research.
 Effective enumeration.
 Effective pre testing.
 Controlling methodological bias.
 Selection of appropriate sampling techniques.
Task- 1
To study the relationship between
Pedometer determined physical activity and
body composition in IT professionals
Quota sampling
Task 2
• A study to assess the ut ilization and level of satisfaction of National
Heal th Mission services by the client’s attending community health
centres
• purposive sampling
Task 3
• Non-Utilization of antenatal care services among women of
reproductive age in the Niger delta region of Nigeria: Findings from
2595 women
• Multistage sampling
Task 4
• Diet Associated Problems and Nutritional Status of Elderly of Selected
Community
• convenience sampling
non probalilty sampling.ppt
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non probalilty sampling.ppt

  • 1. Malar Kodi S Assistant Professor College of Nursing AIIMS Rishikesh
  • 2. Outlines  Sample definition  Purpose of sampling  Process in the selection of a sample  Types of sampling  Non probability sampling technique
  • 3. Sampling is the process of selecting observations (a sample) to provide an adequate description and inferences of the population.
  • 4. What is Sampling? Sampling is the act, process or technique of selecting a suitable sample or a representative part of a population for the purpose of determining parameters or characteristics of the whole population Suitable sample
  • 5. Why Sampling instead of doing a census? Economy Timeliness Large size of population Inaccessibility of some population Destructiveness of the observation Accuracy
  • 7. Population Sample Sampling Frame Sampling Process What you want to talk about What you actually observe in the data Inference
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  • 10. Sampling criteria Inclusion criteria- The criteria that specify population characteristics Exclusion Criteria- A population is defined in terms of characteristics that people must not possess
  • 11. CONCEPTS OF SAMPLING Target population The aggregate of cases about which Researcher would like to generalize Whom do you wish to generalize the findings? Accessible population The aggregate of cases conform to designated criteria and that are accessible Which Population do You have access? Sampling Frame The List or procedure defining the Population (from which the sample will be drawn) E.g Telephone book ,Voters list Through what resource you can access them? Sample Subset of population elements Who is participating in your Study?
  • 12.
  • 14.
  • 15.  All subsets of the frame are given an equal probability.  Random number generators
  • 16. Advantages:  Minimal knowledge of population needed  Easy to analyze data Disadvantages:  Low frequency of use  Does not use researchers’ expertise  Larger risk of random error
  • 17.  Population is divided into two or more groups called strata  Subsamples are randomly selected from each strata
  • 18. Advantages:  Assures representation of all groups in sample population  Characteristics of each stratum can be estimated and comparisons made Disadvantages:  Requires accurate information on proportions of each stratum  Stratified lists costly to prepare
  • 19.  The population is divided into subgroups (clusters) like families.  A simple random sample is taken from each cluster
  • 20. Advantages: Can estimate characteristics of both cluster and population Disadvantages: The cost to reach an element to sample is very high Each stage in cluster sampling introduces sampling error—the more stages there are, the more error there tends to be
  • 21.  Order all units in the sampling frame  Then every nth number on the list is selected  N= Sampling Interval
  • 22. Advantages:  Moderate cost; moderate usage  Simple to draw sample  Easy to verify Disadvantages:  Periodic ordering required
  • 23.
  • 24.  Carried out in stages  Using smaller and smaller sampling units at each stage  Most commonly used sampling design in practice  Involves more than one stage of sampling and/or a combination of two or more sampling designs
  • 25. Advantages:  More Accurate  More Effective Disadvantages:  Costly  Each stage in sampling introduces sampling error—the more stages there are, the more error there tends to be
  • 26.
  • 27.
  • 28.  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 statistical techniques for measuring random sampling error in a non-probability sample.
  • 30.  Convenience sampling involves choosing respondents at the convenience of the researcher .
  • 31. 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.
  • 32. • The population is first segmented into mutually exclusive sub- groups, just as in stratified sampling. • Judgment Used To Select Subjects From Each Segment
  • 33.
  • 34.
  • 35. Advantages  Used when research budget is limited  Very extensively used/understood  No need for list of population elements Disadvantages  Variability and bias cannot be measured/controlled  Time Consuming  Projecting data beyond sample not justified
  • 36.  Researcher employs his or her own "expert”judgment about.  Subjects are selected purposely who are judged to be typical population and knowledgeable about the issues under the study E.g. Home care of Diabetes mellitus, case studies
  • 37. Advantages  There is a assurance of Quality response  Meet the specific objective. Disadvantages  Bias selection of sample may occur  Time consuming process.
  • 38.  The research starts with a key person and introduce the next one to become a chain Network or Chain sampling
  • 39. Advantages  Low cost  Useful in specific circumstances & for locating rare populations Disadvantages  Not independent  Projecting data beyond sample not justified
  • 40.  It occurs when you allow each case usually individuals, to identify their desire to take part in the research.  Select who volunteer for the sample
  • 41. Advantages  More accurate  Useful in specific circumstances to serve the purpose. Disadvantages  More costly due to Advertizing  Mass are left
  • 43. Sampling Error o The Fluctuation of the value of a statistics from one sample to another drawn from the same population o The systematic over- representation or under representation of some segment of the population in terms of a characteristic relevant to the research question
  • 44.
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  • 46.  Specific problem selection.  Systematic documentation of related research.  Effective enumeration.  Effective pre testing.  Controlling methodological bias.  Selection of appropriate sampling techniques.
  • 47.
  • 48.
  • 49. Task- 1 To study the relationship between Pedometer determined physical activity and body composition in IT professionals Quota sampling
  • 50. Task 2 • A study to assess the ut ilization and level of satisfaction of National Heal th Mission services by the client’s attending community health centres • purposive sampling
  • 51. Task 3 • Non-Utilization of antenatal care services among women of reproductive age in the Niger delta region of Nigeria: Findings from 2595 women • Multistage sampling
  • 52. Task 4 • Diet Associated Problems and Nutritional Status of Elderly of Selected Community • convenience sampling