Question

1. How does one go about constructing a sampling frame?

2. When is stratified random sampling more efficient than simple random sampling?

3. When is it advantageous, or even necessary, to employ disproportionate stratified random sampling?

4. When is nonprobability sampling justified?

Answer 1

1. The sampling frame is the list of all subjects or objects that we want to include in the sampling process. It can be constructed by using the appropriate list. For example: Suppose we have a Statistics Class named STAT100 then people in that class will be the Population of the class and the list of names of those students will be sampling frame.

2. The stratified random sampling is more efficient than simple random sampling when the characteristics of the subjects under study are different.

3. When the number of subjects in each stratum is is not same then it is advantageous, or even necessary to employ disproportionate stratified random sampling.

4. Nonprobability sampling is justified when a particular attribute needs to be studied. For example: Suppose we want to study about patients having Lung Cancer and Diabetes 1 then we only need those people who have both of these studies hence we would need to apply nonprobability sampling.