2. Sampling
Sampling is a process used in statistical analysis in which a
predetermined number of observations are taken from a
larger population.
The methodology used to sample from a larger population
depends on the type of analysis being performed, but it
may include simple random sampling or systematic
sampling.
3. Population and Census
Population - A unit, is an entity on which we can make observations according to a well-
defined procedure. The entire collection of such units is called a population or universe.
If the number of units is finite, it is a finite population and if the number of units is infinite,
it is an example of an infinite population. Usually in research ,we are concerned with a
finite population.
Census - When an inquiry is based upon obtaining information from all the units of a
population, the procedure is known as the complete enumeration method or the census
method.
4. Sample , Sampling Frame and Parameter
Sample – It involves collection of a part or section of the population. The procedure of
obtaining a sample is known as sample survey
Sampling Frame - sampling frame is the source material or device from which a sample is
drawn. It is a list of all those within a population who can be sampled and studied
Parameter - In a statistical inquiry, our interest lies in one or more characteristics of the
population. A measure of such a characteristic is called a parameter. For example, in the
mean income of the people of some region for a particular year. Here, both mean and
standard deviation are parameters.
5. Sample Survey
Survey sampling is a statistical process that involves selecting and surveying individuals
from a particular population.There are important advantages of a sample survey- or census
method. Some of these advantages are mentioned below.
i) Practicability
Sometimes, a census may not be practicable due to the enormity of the task required in the
collection of data of a large population In such a situation, a sample
survey may be quite practicable
6. Sample Survey
ii) Speed This may be an important advantage, particularly, when the information is
urgently needed.
iii) Accuracy In any survey, census or sample, the required information is obtained by
filling in the questionnaires. It has been observed that more accurate results are achieved
when the investigator themselves fill in the questionnaire instead of the respondents filling
it. Again, personal interviews may result in more accurate information than sending the
questionnaires to the respondents by post and requesting them to fill in these
questionnaire.
7. Sampling Survey
iv) Cost It is obvious that a sample survey results in less expenditure than a complete enumeration.
After all, in a survey only part of the population is involved. The cost components of an inquiry are:
Overhead cost of the organization conducting the survey,
Cost of collecting the data,
Cost of processing and tabulating the data, and
Cost of publication of results of the survey.
8. Sampling Error
Sampling error is the absolute difference between the parameter and the corresponding
statistic, that is, IT -01.
Sampling error is not due to any lapse on the part of the respondent or the investigator
or some such .reason.
t arises because of the very nature of the procedure.
It can never be completely eliminated. It can be minimised.
9. Differences between Probability & Non -
probability
Non-probability sampling Probability sampling
Sample selection based on the subjective
judgment of the researcher.
The sample is selected at random.
Not everyone has an equal chance to
participate.
Everyone in the population has an equal
chance of getting selected.
The researcher does not consider sampling
bias.
Used when sampling bias has to be reduced.
Useful when the population has similar
traits.
Useful when the population is diverse.
The sample does not accurately represent the
population.
Used to create an accurate sample.
Finding respondents is easy. Finding the right respondents is not easy.
10. TYPES OF SAMPLING
Probability Sampling
It is-also called random sampling.
It is a procedure in which every member of the population has a chance or probability of
being selected in the sample. It is in this probabilistic sense that the sample is random.
The word 'random' does not mean that the sample is obtained in a haphazard manner
without following any rule.
Random sampling is based on the well-established principles of probability theory.
11. Probability Sampling Methods
Simple Random Sampling
If there is not much variation in the characteristics of the members of a population, we
follow the method of simple random sampling. In this method, we consider the
population in its entirety as a homogeneous group and follow the principle of random
sampling to choose the members for the sample.
12. Probability Sampling Methods
Systematic Random Sampling - In this variant of random sampling, only the first unit of the
sample is selected at random from the population. The subsequent units are then selected by
following some definite rule.
Stratified Random Sampling -Stratified random sampling is the appropriate method if the
population consideration consists of heterogeneous units. Here, first we divide the population
into certain homogeneous groups or strata. Secondly, from each stratum some units are selected
by simple random sampling. Thirdly, after selecting the units hm each stratum, they are mixed
together to obtain the final sample.
13. Probability Sampling Methods
Multi-Stage Random Sampling - Multistage sampling is defined as a sampling method that
divides the population into groups (or clusters) for conducting research. ..During this sampling
method, significant clusters of the selected people are split into sub-groups at various stages to
make it simpler for primary data collection.
14. Non-Probability Sampling
Non-probability sampling is a sampling method in which not all members of the
population have an equal chance of participating in the study, unlike probability
sampling.
Each member of the population has a known chance of being selected. Non-probability
sampling is most useful for exploratory studies like a pilot survey (deploying a survey
to a smaller sample compared to pre-determined sample size).
Researchers use this method in studies where it is impossible to draw random
probability sampling due to time or cost considerations.
15. Convenience & Quota sampling
It is a non-probability sampling technique where samples are selected from the
population only because they are conveniently available to the researcher.
Researchers choose these samples just because they are easy to recruit, and the
researcher did not consider selecting a sample that represents the entire population.
Quota - This type of sampling is preferred , when the researcher is interested in
particular strata within the population. Here is where quota sampling helps in dividing
the population into strata or groups
16. Purposive / Snow ball sampling:
Purposive sampling method, researchers select the samples based purely on the researcher’s knowledge
and credibility. In other words, researchers choose only those people who they deem fit to participate in
the research study. Judgmental or purposive sampling is not a scientific method of sampling, and the
downside to this sampling technique is that the preconceived notions of a researcher can influence the
results. Thus, this research technique involves a high amount of ambiguity.
Snowball sampling: helps researchers find a sample when they are difficult to locate. Researchers use this
technique when the sample size is small and not easily available. This sampling system works like the
referral program. Once the researchers find suitable subjects, he asks them for assistance to seek similar
subjects to form a considerably good size sample.
