2. Census: A census is the procedure of systematically acquiring and
recording information about the members of a given population.
It is a regularly occurring and official count of a particular
population.
The term is used mostly in connection with national population and
housing censuses; other common censuses include agriculture,
business, and traffic censuses.
A survey that measures the entire target population is called a
census.
3. What is Sample
A sample is a subset of the population.
It comprises some members selected from it. In other words, some,
but not all, elements of the population would form the sample.
According to E.R Babble “A sample is a special subset of
population that is observed for purpose of making inference about
the nature of the total population itself .”
Example:
if there are 145 in-patients in a hospital and 40 of them are to be
surveyed by the hospital administrator to assess their level of
satisfaction with the treatment received, then these 40 members will
be the sample.
4. Sampling Survey
The sample survey was only a small size but it did give us a
window of knowledge and understanding . The sample
survey that we gave to the public was given in order to
determine what we needed to do.
A sample survey can often change the design of a product or
even the entire product as a whole, depending on current
consumer opinions.
5. Difference between Census and sampling
In Census, each and every unit of population is studied.
But only few units of the population is studied in Sampling.
Census refers to periodic collection of information about the
populace from the entire population.
However, if the next Census is far away, Sampling is the
most convenient method of obtaining data about the population.
Census Method demands a large amount of finance, time and
labor.
Relatively less amount of finance, till labor is required for
sampling.
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Results obtain by the Census are quit reliable.
Results obtained by the Sampling are less reliable.
It is more suitable to use Census Method if population is
heterogeneous in nature.
and it is more suitable to use Sampling Method if population
is homogeneous in nature.
Samples have a margin of error though, which gets lower as the
sample size increases. In other words sampling more people
means obtaining better data.
Instead, this type of error not present in Census as each and
every part of the geographical area has to be approached for data
collection .
7.
8. Sample Design
A sample design is the framework, or road map, that serves as the
basis for the selection of a survey sample and affects many other
important aspects of a survey as well.
In broad context survey researchers are interested in obtaining
some types of information through a survey for some population
or universe. One must define a sampling frame that represents
the population of interest from which a sample is to be drawn.
9. Following are the characteristics of good
sample design:
1. Sample design should be a representative sample: A researcher
selects a relatively small number for a sample from an entire
population. If the sample used in an experiment is a
representative sample then it will help generalize the results from
a small group to large universe being studied.
2. Sample design should have marginal systematic bias: Systematic
bias results from errors in the sampling procedures which cannot
be reduced or eliminated by increasing the sample size. The best
bet for researchers is to detect the causes and correct them.
3. Results obtained from the sample should be generalized and
applicable to the whole universe: The sampling design should be
created keeping in mind that samples that it covers the whole
universe of the study and is not limited to a part.
10. Types of sample design
Probability samples: Probability sampling technique is one in
which every unit in the population has a chance of being selected in
the sample.
Non-probability samples: Non probability sampling in any
sampling method where some elements of the population have no
chance of selection, or where the probability of selection can’t be
accurately determined.
•It involves the selection of elements based on assumptions.
•The selection of elements is non random.
11.
12. Simple Random Sampling Design: Each element or each
combination of elements has equal probability of selection.
Applicable when population is small , homogeneous &
readily available.
A table of random number or lottery system is used to
determine which are to be selected.
Systematic Sampling Design: Systematic sampling relies on
arranging the target population according to some ordering
scheme & then selecting elements at regular intervals.
Each element has equal probability of selection but
combination of elements have different probabilities.
13. Stratified Sampling Design: Where population embraces a
number of distinct categories then the population is broken
down into separate groups in which each group is sampled
as sub-population & a random sample is taken of each
category.
•Every unit in a group has same chance of being selected.
•Probabilities of selection may be different for different
groups.
14. Cluster sampling: Cluster sampling is a sampling
technique used when "natural" but relatively homogeneous
groupings are evident in a statistical population.
•It is often used in marketing research.
•In this technique, the total population is divided into these
groups (or clusters) and a simple random sample of the
groups is selected.
Multistage sampling: Complex form of cluster sampling in
which two or more levels of units are embedded one in the
other.
•First stage, random number of districts chosen in all
states.
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• Followed by random number of talukas , villages.
• Then third stage units will be houses
• This technique, is essentially the process of taking
random samples of preceding random samples.
• Multistage sampling used frequently when a
complete list of all members of population not
exists is appropriate.
16. Multiphase sampling: In multiphase sampling the
different phase of observations relate to the sample
units of the same type.
•Part of the information collected from sample &
subsample .
•Survey by such procedure is less costly , less
laborious & more purposeful
17. Non-probability samples:
Convenience Sampling: Sometimes known as grab
or opportunity sampling or accidental or haphazard
sampling.
Purposive sampling:the process whereby the
researcher selects a sample based on experience or
knowledge of the group to be sampled
…called “purposive” sampling
18. Judgmental Sampling: The researcher chooses
the sample based on who they think would be
appropriate for the study.
This is used primarily when there is a
limited number of people that have expertise in
the area being researched.
