This document discusses census and sampling methods for collecting population data. A census collects data from all members of the population, while sampling collects data from only a subset. Sampling is faster, cheaper, and more adaptable than a census but less accurate. Probability sampling methods like simple random and stratified random sampling allow accurate error estimation, while non-probability methods do not. Both methods have advantages and disadvantages related to accuracy, costs, and error estimation. The document also defines sampling error and non-sampling error and their sources.

1. CENSUS VS SAMPLING
PROBABILITY & NON -PROABILITY
SAMPLING
SAMPLING & NON -SAMPLING ERROR
PRESENTED BY:
DHIRESH CHAWLA
SUNIL CHICHRA
VIVEK PANDEY

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 n 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 n Cons of SAMPLING Method
 Low Cost
 Less Time
 Representative Average results
 Not representative total population
 Not suitable for producing benchmark data

7. Probability Sampling
 Also known as Random Sampling
 Randomly selection of samples
 In this probability can be accurately determined
 Includes :
 Simple Random Sampling
 Systematic Random Sampling
2nd sample are taken at Interval
 Stratified Random Sampling
Relevant subgroups created

8. Simple
Systematic
Stratified

10. Non-Probability Sampling
 Also known as Non-Random Sampling
 Selection is non-random & probability of their selection
cannot be determined
 Includes :
 Convenience Sampling
Based on ease of access
 Purposive Sampling
Based on what researcher think
 Quota Sampling
Based by defined quotas
 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

14. 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 the sample
Statistical Errors are sample error

15.  Causes :




Faulty Selection Of Sample
Substitution
Faulty Demarcation of sampling units
Two types of error
1. Biased error
2. Unbiased error

16. 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

17.  Arises From :
Lack of Trained & experienced Investigators

Errors committed during presentation

Duplication of units

Defective frames & faulty selection of samples
units

Lack of adequate inspection & supervision of
primary staff

Errors in data processing operation like as
coding, tabulation etc.
