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DIFFERENT T YPES YPES OF SAMPLING DESIGNS SHINCE PETER MS
DIFFERENT TYPES OF SAMPLE DESIGNS
There are different type of sample designs based on two factors:
The representation basis .
Element selection technique.
¶On the representation basis, the sample may be probability sampling or it may be non-probability sampling.·
¶On the element selection basis the sample may be restricted or unrestricted.·
Sample designing are basically of two types.
Non
Probability sampling.
probability sampling.
NON-P NO N-PROB ROBABI ABILIT LITY Y SAM SAMPLIN PLING G Non
prob pr obab abil ilit ity y sa samp mpli ling ng is th that at sa samp mpli ling ng
proc pr oced edur ure e wh whic ich h doe oess not af affo ford rd an any y ba basi siss fo forr estimating the probability that each item in the population has of being included in the sample.
Non
probability sampling is also known by
diff di ffer eren entt na name mess su such ch as de deli libe bera rate te sa samp mpli ling ng,, purposive sampling and judgment sampling.
In
this type of sampling, items for the sample are
selected deliberately by the researcher; his choice concerning the items remains supreme.
Under non-probability sampling the organizer of the th e in inqu quir iry y pu purp rpos osiv ivel ely y ch choo oose se th the e par arti ticu cula larr units of the universe for constituting a sample on the basis of that the small mass they so select out of a huge one will be typical or representative of the whole.
Non
probability sampling design is rarely adopted in large enquiries of importance
In
small enquiries and researches by individuals this design is adopted because of the relative advantage of time and money.
Sampling
error in this type of sampling cannot be estimated and the element of bias, great or small is always there.
EXAMPLE: If economic conditions of people living in a state are to be studied, a few towns and villages may be selected for intensive study on the principle that they can be representative of the entire state.
CITING
In
THE EXAMPLE OF QUOTA SAMPLING
quota sampling the interviewers are simply given
quotas to be filled from the different strata with w ith some restrictions on how they are to be filled.
Here the actual selection of the items for the sample is left to the interviewer·s discretion.
Convenient and relatively inexpensive.
But the samples so selected may not possess the characteristics of random samples.
They are essentially judgment samples.
PROBABILITY SAMPLING
Probability sampling is also known as ¶random sampling· or ¶chance sampling'.
Under this sampling design, every item of the universe has an equal chance of inclusion in the sample.
It
is a lottery method in which individual units are picked up from the whole not deliberately but by some mechanical process.
Citing the example of Random sampling
It
ensures the law of statistical regularity which
states that if on an average the sample chosen is a random one, the sample will have the same composition and characteristics as the universe.
Therefore random sampling is considered considered as the best technique of selecting a representative sampling
Once an item is selected for the sample, it cannot appear in the sample again.
The implications of random sampling are
It
gives each element in the population an equal
probability of getting into the sample:and all chices are independent of one another.
It
gives each possible sample combination co mbination an
