Answer to Question #201380 in Statistics and Probability for Junaid Ahmed

Question

a) Identify and shortly explain in what conditions researchers use random and non-random sampling techniques.

b) Differentiate stratified and cluster sampling with examples.

Answer 1

a)

RANDOM SAMPLING:

We use random sampling method whenever the following conditions are met:

(1) Every element in our population has a nonzero probability of being selected as part of the sample.

(2) We have accurate knowledge of this probability, known as the inclusion probability, for each element in the sampling frame.

If both of these conditions are met, it is possible to obtain unbiased results about the population from studying the sample and samples obtained under these conditions are also known as random samples.

NON-RANDOM SAMPLING:

All that said, it’s not easy to meet the criteria imposed by random sampling:

(1) It is relatively unusual to have a sampling frame available to you when you’re conducting market studies.

(2) Ensuring that the every individual in a population has a nonzero probability of being selected is just as difficult to accomplish; knowing every sampling unit’s exact inclusion probability is even more difficult. The individuals that cannot be selected as part of a sample are generally referred to as excluded units.

For these reasons—and to minimize costs—researchers often turn to other sampling methods, known as non random sampling and the samples obtained under these conditions are called non random samples.

b) Comparison:

1.)Definition:

Cluster Sampling: Members of the cluster sampling are chosen from naturally divided groups called clusters, by randomly selecting elements to be a part of the sample.

Stratified Sampling: Members of the stratified sampling are randomly chosen from non-overlapping, homogeneous strata.

2.)Purpose:

Cluster Sampling: Main purpose is Cost reduction and increased efficiency.

Stratified Sampling:Main purpose is Enhanced precision and population depiction.

3.)Sample selection:

Cluster Sampling: Selection of the samples is done by the randomly selected clusters and including all the members from these clusters.  

Stratified Sampling: Selection of the sample is done by the randomly selecting members from various formed strata.

4.)Division type:

Cluster Sampling: Naturally Formed

Stratified Sampling: Depends on the researcher.