Types of SamplingIt can be divided into two groups :
i. Probability sampling
ii. Non-probability sampling
i. Probability sampling :
Such a sampling including principles of sampling unit-principles of randomness is called probability sampling.
It is the real representative sampling of population. A researcher establishes a relation between universe and sampling making the research more trustworthy.
It can further be divided into three kinds:
A. Simple Random sampling
B. Stratified sampling
C. Cluster sampling
A. Simple Random Sampling :Simple Random sampling is the most simple in the probability sampling. It can easily be understood and used. A researcher can prepare a frame for sampling easily and can select sampling units in a correct manner because in the presence of sampling frames, mathematical random procedure can be done easy. For example we want to make a simple random sampling 36 homes whereas our universe or population consists of 144 homes. We will adopt a procedure given below :
Universe ----- 144 homes
Sample size ----- 36 homes
Sampling unit ----- A home
Now a proportion of sampling according to target sampling is prepared.
Proportion = Size of sampling = 0.25 or 25%. It means that every fourth house is becoming part of sampling.
Merits of Simple Random Sampling1. It is less costly. The only expenditure is on the collection. of target population.
2. It can easily be got. No special mathematical procedures are required.
3. No need of being more personal. Even the researcher can make the sampling himself.
4. This is used for homogeneous population having likely characteristics and the consequences of the research can be applied to the population.
Demerits of Simple Random Sampling1. It cannot used for Heterogeneous population.
2. It cannot be used for a complicated and vast population because its sampling is not a real representative of the population.
B. Stratified Sampling :Such a heterogeneous population having no equal characteristics of sampling unit. Here stratified sampling is used. The researcher first of all divides the heterogeneous population into strata and after that keeping this size of the sampling in mind gets a proportionate number sampling from every strata. Thus there is a representative of every strata in the whole sample of the strata. For example, there are 144 homes in a village. The residents of these homes are divided into four strata A, B, C and D, according to the economic
condition. Every strata has a different number of homes. By this method, economically heterogeneous population has been divided into small heterogeneous economic strata.
Strata A 40 homes
Strata B 60 homes
Strata C 24 homes
Strata D 20 homes
Size of the sampling = 36 homes
With this reference the proportion of the sampling strata will be :
Size of Sampling strata A =
So 40 homes strata A will include 10 homes in the sampling. Similarly,
60 homes of strata B will have 15 times in the sampling.
24 homes of strata D will have 6 homes in the sampling
20 homes of strata D will have 5 homes in the sampling.
This will be called a stratified sampling of population of 144 consisting of a sample of 36 homes