Page 78 - DMGT404 RESEARCH_METHODOLOGY

Research Methodology

Notes Non-probability Sample

In this case, the likelihood of choosing a particular universe element is unknown. The sample
chosen in this method is based on aspects like convenience, quota etc.

Example: Quota sampling and Judgment sampling.

Difference between Cluster Sampling and Stratified Random Sampling

The major difference between cluster sampling and stratified sampling lies with the inclusion of
the cluster or strata. In stratified random sampling, all the strata of the population is sampled
while in cluster sampling, the researcher merely randomly selects a number of clusters from the
collection of clusters of the entire population. Thus, only a number of clusters are sampled, all
the other clusters are left unrepresented.
The other notable differences between Cluster and Stratified random sampling are as follows:

 When natural groupings are clear in a statistical population, cluster sampling technique is
used. While Stratified sampling is a method where in, the member of a group are grouped
into relatively homogeneous groups.

 Cluster sampling can be chosen if the group consists of homogeneous members. On the
other hand, for heterogeneous members in the groups, stratified sampling is a good
option.
 The benefit of cluster sampling over other sampling methods is, it is cheaper as compared
to the other methods. While the benefits of stratified sampling are, this method ignores
the irrelevant ones and focuses on the vital sub populations. Another advantage is, with
stratified random sampling method is that for different sub populations, the researcher
can opt for different sampling techniques. The stratified sampling method as well helps in
improving the efficiency and accuracy of the estimation and facilitates greater balancing
of statistical power of tests.
 The major disadvantage of cluster sampling is, it initiates higher sampling error. This
sampling error may be represented as design effect. The disadvantages of stratified random
sampling method are, it calls for choice of relevant stratification variables which can be
tough at times. When there are homogeneous subgroups, random sampling method is not
much useful. The implementation of random sampling method is expensive and If not
provided with correct information about the population, then an error may be introduced.
 All strata are represented in the sample; but only a subset of clusters are in the sample.

Self Assessment

Fill in the blanks:
7. Sampling is divided into two types, viz. ...................... and ......................

8. There are ...................... methods used in the random sampling.
9. ...................... is also called as the random sampling with replacement.
10. ...................... is also called random sampling without replacement.
11. Stratified sampling can be carried out with ...................... proportion across the strata
proportionate stratified sample.

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