Census collects data from the entire population, while sampling collects data from only a subset of the population. Sampling provides results more quickly and at lower cost but with less accuracy than a census. Probability sampling methods like simple random sampling, systematic sampling, and stratified sampling allow determining the probability of selecting samples, while non-probability methods do not. Both methods have advantages and disadvantages related to accuracy, costs, and ability to generalize to the total population. Errors can occur from how samples are selected and from other issues in data collection and processing.

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

8. Simple
Systematic
Stratified

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.