The document discusses sampling methods for research studies. It defines key sampling terms like population, sample, sampling frame, and probability and non-probability sampling. It describes different sampling designs such as simple random sampling, stratified sampling and cluster sampling. Factors that influence sample size decisions and sampling quality are also covered, such as ensuring a representative sample, minimizing bias and achieving data saturation. Different sampling techniques are discussed for both quantitative and qualitative research methodologies.

1. SAMPLING
Dr. Jayesh Patidar
www.drjayeshpatidar.blogspot.com
9/30/2015 1

2. Population
Definition:
The term population refers to the
aggregate or totality of all the objects,
subjects, or members that conform to a
set of specifications.
The Accessible Population
• The aggregate of cases
• Conform to the designated criteria
• Accessible to the researcher
SAMPLING

3. The Target Population
• The aggregate of cases
• The researcher would like to make
generalizations
Criteria
• Eligibility criteria or inclusion criteria
• Exclusion criteria
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4. Sample
Definition: Sample is a subgroup of the population. It is
defined as a collection of individual observations from
the population about which inferences are to be made,
and is obtained by a specific method.
Sampling: It refers to the process of selecting a portion of
the population to represent the entire population.
Sample and Sampling
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5. Aim of sampling:
• To draw valid inferences about the population parameters
using the sample statistics
Theory of sampling
This is based on
• The law of statistics regularity
• The law of inertia of large numbers
Some Terminology
• Element – The most basic unit of a population from which a
sample will be drawn.
• Representative sample-A sample whose characteristics are
highly similar to those of the population from which it is drawn.
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6. • Strata -Subdivisions of the population according to some
characteristic.
• Sampling bias- Refers to the systematic over
representation or under representation of some segment
of the population in terms of a characteristic relevant to
the research question.
• Sampling distribution -A theoretical distribution of a
statistic using the valves of the statistic computed from
an infinite number of samples as the data points in the
distribution.
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7. • Sampling error -Refers to differences between populations values
and sample values
• Sampling frame -A list of all the elements in the population, from
which the sample is drawn
• Sampling frame-A list of all the elements in the population, from
which the sample is drawn
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8. Sampling designs
• Probability sampling
• Non probability sampling
Non probability sampling
• It is less likely to produce accurate and
representative samples than probability
sampling.
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9. Methods
• Convenience sampling.
• Snowball sampling or network sampling.
• Quota sampling.
• Purposive sampling or judgmental
sampling.
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10. Probability sampling
Methods
• Simple random sampling
• Stratified random sampling
• Cluster sampling or multistage sampling
• Systematic sampling
Sample size
• Estimated using a procedure known as power
analysis
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11. Factors that Affect Sample Size
Decisions
• Homogeneity of the population
• Effect size
• Attrition
• Number of variables
• Subgroup analyses
• Sensitivity of the measures
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12. Steps in sampling
• Identify the target population
• Identify the accessible population
• Specify the eligibility criteria
• Specify the sampling plan
• Recruit the sample
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13. Factors that Influence the Rate of
Co-operation
• Method of recruitment
• Pleasantness of the recruiters
• Persistence
• Payment of an incentive
• Explanation of research benefits
• Offers of a research summary
• Making participation convenient
• Endorsements
• Assurances of research integrity
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14. Tips for Sampling
• Identify important extraneous variables
• Select study participants from two or more sites
• Understand and document who the participants
are
• As you recruit, document thoroughly
• Develop contingency plans for recruiting more
subjects.
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15. Sampling in qualitative research
Types of qualitative sampling
• Convenience sampling
• Snow ball sampling
• Theoretical sampling
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16. Sample size - Data saturation
Sampling process
• Selection on the basis of convenience or snow-balling or both
methods.
•
• Sample selection serially ratter then up-front
• Informants are often used to facilitate the selection
• The sample is adjusted in an ongoing fashion
• Sampling continues until saturation is achieved
• Final sampling includes a search for confirming and non-
confirming cases.
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17. Thank you
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