Sample and Sampling designs

ample and Sampling design
by Vinay Teja

The process used to collect information and
data for the purpose of making business
decisions.
The methodology may include publication
research, interviews, surveys and other
research techniques, and could include both
present and historical information.
Research:

The research methodology may include
 Publication research
 Interviews
 Surveys and other research techniques
(It could include both present and historical
information)
Research:

Why research is required?
 It is the fountain of knowledge and provide
guidelines for solving problems.
 It is important in industry and business for higher
gain and productivity and to improve the quality of
products.
 Mathematical and logical research on business and
industry optimizes the problems in them.

Why research is required?
 It leads to the identification and characterization of
new materials, new living things.
 Social research helps find answers to social
problems. They explain social phenomena and seek
solution to social problems.

Steps in research methodology:

Sampling:
Sampling is the process of selecting units
(e.g., people, organizations) from a
population of interest so that by studying the
sample we may fairly generalize our results
back to the population from which they were
chosen.

Get information about large populations
 Lower cost
 More accuracy of results
 High speed of data collection
 Availability of Population elements.
 Less field time
 When it’s impossible to study the whole population
Why Sampling is required?

The representation basis:-
 Random sampling(Probability)
 Non-Random sampling(Non-Probability)
Element selection technique:-
 Restricted sampling
 Un-Restricted sampling
Types of Sampling:

Types of Sampling:
Random sample:-
It is a method of sampling that uses of random
selection so that all units/ cases in the population
have an equal probability of being chosen.
Non-Random sample:-
It does not involve random selection and methods are
not based on the rationale of probability theory.

Random Sampling:
Types of random sampling:-
 Simple random sample
 Systematic random sample
 Stratified random sample
 Cluster sample

Simple random sampling:
 It is applicable when population is Small,
Homogeneous & Readily available.
Advantages:-
1. Easy method to use.
2. No need of prior information of population.
3. Equal and independent chance of selection to every
element.
Disadvantages:-
1. If sampling frame large, this method impracticable.
2. Does not represent proportionate representation.

Simple random sampling:

Systematic random sampling:
 Similar to simple random sample. No table of
random numbers – select directly from
sampling frame. Ratio between sample size and
population size

Advantages:-
1. Sample easy to select
2. Suitable sampling frame can be identified easily
3. Sample evenly spread over entire reference population
4. Cost effective
Disadvantages:-
1. Sample may be biased if hidden periodicity in population
2. Coincides with that of a selection.
3. Each element does not get equal chance
4. Ignorance of all element between two n element

Stratified random sampling:
 The population is divided into two or more groups
called strata, according to some criterion, such as
geographic location, grade level, age, or income, and
subsamples are randomly selected from each strata

Advantages:-
1. Enhancement of representativeness to each sample.
2. Higher statistical efficiency.
3. Easy to carry out.
Disadvantages:-
1. Classification error.
2. Time consuming and expensive.
3. Prior knowledge of composition and of distribution of
population.

Cluster random sampling:
 The population is divided into subgroups
(clusters) like families. A simple random
sample is taken of the subgroups and then all
members of the cluster selected are surveyed.

Cluster sampling consists of two stages.
 First stage a sample of areas is chosen.
 Second stage a sample of respondents within those
areas is selected.
 Population divided into clusters of homogeneous
units, usually based on geographical contiguity.
 Sampling units are groups rather than individuals.
 A sample of such clusters is then selected.
 All units from the selected clusters are studied.

Advantages:-
 Cuts down on the cost of preparing a sampling
frame. This can reduce travel and other administrative
costs.
Disadvantages:-
 Sampling error is higher for a simple random
sample of same size.

Errors in sampling:
Non-Observation Errors:-
 Sampling error: naturally occurs
 Coverage error: people sampled do not match
the population of interest
 Underrepresentation
 Non-response: won’t or can’t participate

Characteristics of sampling:
 Much cheaper.
 Saves time.
 Much reliable.
 Very suitable for carrying out different surveys
 Scientific in nature.

Advantages in sampling:
 Very accurate
 Economical in nature.
 Very reliable.
 High suitability ratio towards the different surveys.
 Takes less time.
 In cases, when the universe is very large, then the
sampling method is the only practical method for
collecting the data.

Disadvantages in sampling:
 Inadequacy of the samples.
 Chances for bias.
 Problems of accuracy.
 Difficulty of getting the representative sample.
 Untrained manpower.
 Absence of the informants.
 Chances of committing the errors in sampling.

Sample and Sampling designs

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