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CENSUS VS SAMPLING
PROBABILITY & NON-PROABILITY
SAMPLING
SAMPLING & NON-SAMPLING ERROR
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
 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
 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
Pros & Cons of Census
Method
True Measure
Benchmark data obtained for future studies
Detailed information for sub-groups
Higher costs
Long time to collect & process
Difficult to enumerate
Pros & Cons of Sampling Method
 Low Cost
 Less Time
 Representative Average results
 Not representative total population
 Not suitable for producing benchmark data
Probability Sampling
o Also known as Random Sampling
o Randomly selection of samples
o In this probability can be accurately determined
Includes :
Simple Random Sampling
Systematic Random Sampling
2nd sample are taken atInterval
Stratified Random Sampling
Relevant subgroups created
Simple
Systematic
Stratified
Non-Probability
Sampling
o Also known as Non-Random Sampling
o Selection is non-random & probability of their selection
cannot be determined
 Includes :
o Convenience Sampling
Based on ease of access
o Purposive Sampling
Based on what researcher think
o Quota Sampling
Based by defined quotas
o Volunteer Sampling
Internet based opinion survey
Advantages & Disadvantage
Probability Sampling
 Reliable
 Easy estimation of errors
 Costly to select
 Need skilled Manpower
 Sample may not provide required data in some cases
Advantages & Disadvantages
Non- Probability Sampling
 Easy & cheap to select
 Data easily obtained
 Understood easily
 Sampling errors can’t estimated
 Variability Can’t Measured or controlled
Sampling Error
Error caused by the act of taking a sample
They cause sample results to be different from the
results of census
Differences between the sample and the population that
exist only because of the observations that happened to
be selected for thesample
Statistical Errors are sampleerror
 Causes :
 Faulty Selection Of Sample
 Substitution
 Faulty Demarcation of sampling units
 Two types of error
1. Biased error
2. Unbiased error
Non - Sampling Errors
 Arises from other types of errors than from a sample
Ex: Tabulation errors
 Occur at every stage at the planning or execution of
census or sample survey
 Also Call as Systematic Error
 Not controlled by sample size
 Arises From :
Lack of Trained & experienced Investigators
Errors committed during presentation
Duplication of units
Defective frames & faulty selection of samples unit
Lack of adequate inspection & supervision of primary
staff
Errors in data processing operation like as coding,
tabulation etc.

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Census and sampling

  • 1. CENSUS VS SAMPLING PROBABILITY & NON-PROABILITY SAMPLING SAMPLING & NON-SAMPLING ERROR
  • 2. 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
  • 3.  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
  • 4.  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
  • 5. Pros & Cons of Census Method True Measure Benchmark data obtained for future studies Detailed information for sub-groups Higher costs Long time to collect & process Difficult to enumerate
  • 6. Pros & Cons of Sampling Method  Low Cost  Less Time  Representative Average results  Not representative total population  Not suitable for producing benchmark data
  • 7. Probability Sampling o Also known as Random Sampling o Randomly selection of samples o In this probability can be accurately determined Includes : Simple Random Sampling Systematic Random Sampling 2nd sample are taken atInterval Stratified Random Sampling Relevant subgroups created
  • 9.
  • 10. Non-Probability Sampling o Also known as Non-Random Sampling o Selection is non-random & probability of their selection cannot be determined  Includes : o Convenience Sampling Based on ease of access o Purposive Sampling Based on what researcher think o Quota Sampling Based by defined quotas o Volunteer Sampling Internet based opinion survey
  • 11. Advantages & Disadvantage Probability Sampling  Reliable  Easy estimation of errors  Costly to select  Need skilled Manpower  Sample may not provide required data in some cases
  • 12. Advantages & Disadvantages Non- Probability Sampling  Easy & cheap to select  Data easily obtained  Understood easily  Sampling errors can’t estimated  Variability Can’t Measured or controlled
  • 13. Sampling Error Error caused by the act of taking a sample They cause sample results to be different from the results of census Differences between the sample and the population that exist only because of the observations that happened to be selected for thesample Statistical Errors are sampleerror
  • 14.  Causes :  Faulty Selection Of Sample  Substitution  Faulty Demarcation of sampling units  Two types of error 1. Biased error 2. Unbiased error
  • 15. Non - Sampling Errors  Arises from other types of errors than from a sample Ex: Tabulation errors  Occur at every stage at the planning or execution of census or sample survey  Also Call as Systematic Error  Not controlled by sample size
  • 16.  Arises From : Lack of Trained & experienced Investigators Errors committed during presentation Duplication of units Defective frames & faulty selection of samples unit Lack of adequate inspection & supervision of primary staff Errors in data processing operation like as coding, tabulation etc.