RESEARCH METHODOLOGY (PRINCIPAL OF SAMPLING)

PRINCIPLES OF SAMPLING

1) Law of statistical regularity- According to this law a group of objects chosen at random from larger group tens to possess the
characteristics of that large group.

2) Principle of inertia of large number- It states that as the sample size increases the result tends to be more reliable & accurate
keeping other things constant.

3) Principle of persistence of small numbers- According to this principle if some of the items in a population possess markedly
distinct characteristic from the remaining items then this tendency would be revealed in the sample value also rather this tendency
of persistence will be there even if the population size is increased or even in the case of large sample.

4) Principle of validity- A sample design is termed as valid if it enables us to obtain valid tests & estimates about the population
parameters.

5) Principle of optimization- this principle stresses the need of obtaining optimum results in terms of efficiency cost of the sample
design with the source available at our disposal.

▪Type 1 error- when we reject the true null hypothesis it is also known as producer error, level of significance and alpha.

▪Type 2 error- when we accept the wrong null hypothesis it is also known as consumer error, ;β-1), power function test or power
curve beta.

▪Standard error- standard deviation of the distribution of the sample mean is known as standard error. S.E=σ/√N.

TYPES OF SAMPLING

PROBABILITY SAMPLING/ RANDOM SAMPLING

1) Random sampling- In random sampling we select the sample randomly i.e. there is equal chance of selecting every item but it is a
case of without replacement. If we select ball from 10 balls then 1/10, if we select 1 ball keeping 1 ball outside then 1/9.

2) Simple random sampling- In simple random sampling we select the sample randomly and there is equal chance of selecting every
item and replacement occurs so size remain the same.eg if we select 1 ball from ten balls after replacement then 1/10 (tibbet
tables/lottery)

3) Stratified sampling- In this type of sampling we convert heterogeneous data in homogenous form and then select the sample
randomly (strata means layers e.g. if we separate boys & girls and then select)

4) Systematic sampling –In this type of sampling we follow a system for collecting a sample on our own and rest of the sample are
automatically selected at equal gal from each other.

5) Cluster sampling- It is also known as area sampling, In this type of sampling we make groups out of heterogeneous data and then
select the groups randomly.

6) Multi stage sampling- In this type of sampling we use same or different method of sampling to study the cases.

NON RANDOM SAMPLING/ NON PROBABILITY SAMPLING

1) Purposive sampling- In this type of sampling the conclusion is predetermined and then we select the sample accordingly.

2) Convenience sampling- It is also known as chunk sampling, incidental sampling and in this type of sampling we get the sample in a
convenient way from collections and guidance.

3) Judgmental sampling- In this type of sampling we collect our sample on the basis of experience, expert knowledge and accordingly
to judge.

4) Quota sampling- In this type of sampling quota is fixed for every enumerators and they have to collect the sample by using any
biased method.

5) Snowball sampling- In this type of sampling we study the rare cases such as aids patients and then accordingly to the reference we collect the sempale.