Sampling Techniques - Random and Non Random, Probabilistic and Non Probabilistic

1. Dr S S N Raju Indukoori
SAMPLING TECHNIQUES

2. TYPES OF SAMPLING TECHNIQUES
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Based on Restriction
1) Unrestricted
2) Restricted
Based on Probability
1) Non Probabilistic Sampling
2) Probabilistic Sampling

3. NON PROBABILITY SAMPLING
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• Unrestricted: It is convenience sampling, as a choice of sample
• Restricted
1) Purposive or Judgmental Sampling
a. Deviant Case: Avoid Problematic
b. Quota Sampling: Group of small size
c. Ad hoc Quotas: Limited size within group
2) Snowball Sampling: Referrals

4. NON PROBABILITY SAMPLING
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Reasons to use
• Procedure satisfactorily meets the sampling objectives
• Lower Cost
• Limited Time
• Not as much human error as selecting a completely
random sample.
• Total list population not available

5. PROBABILITY SAMPLING
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• Unrestricted : Simple random
• Restricted : Complex Probability Sampling
1. Systematic Sampling
2. Stratified Sampling
• Proportionate
• Disproportionate
3. Cluster Sampling.
4. Double / Multiphase Sampling.

6. SIMPLE RANDOM SAMPLING
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• Unrestricted and provide a known non zero probability.
• Purest form of probability Sampling
SizePopulation
SizeSample
SelectionofyProbabilit 

7. COMPLEX RANDOM SAMPLING
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1. Systematic Sampling
2. Stratified Sampling
• Proportionate
• Disproportionate
3. Cluster Sampling.
4. Double / Multiphase Sampling.

8. 1. Systematic Sampling
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• Every kth element is sampled.
• Skip interval is known as kth element.
• Simple and flexible
Process
• Identify, list and number the elements in the population skip
interval (k)
• Identify the random start
• Draw a sample by choosing every kth entry
SizeSample
SizePopulation
intervalskipk 

9. 2. Stratified Sampling
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• Population divided into sub categories (strata).
• Strata is selected based on some criteria
• Strata is homogeneous internally and
heterogeneous externally.
• Elements in strata are selected randomly

10. 2. Stratified Sampling
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Objective is to
1. increase sample’s statistical efficiency
2. Provide adequate data for analyzing strata
3. enable different research methods and procedures to be used in
different strata.
Types
• Proportional to population
• Disproportional to population

11. 3. CLUSTER SAMPLING
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• Population divided into sub groups (Clusters).
• Clusters are selected randomly
• Clusters are heterogeneous internally and homogeneous
externally.

12. 3. Cluster Sampling
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Objective is to increase economic efficiency.
Types
• Area Sampling for geographic area
• Double / Sequential / Multiphase Sampling

13. TYPES OF SAMPLING TECHNIQUES
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Element of
Selection
Non Probability Probability
Unrestricted Convenience Sampling Simple Random
Restricted Judgment Sampling
Deviant Case, Quota, Adhoc
Quota
Systematic Sampling
Snow Ball Sampling Cluster Sampling
Stratified Sampling
Double Sampling