8. Why choose stratified sampling? Mention two main reasons. 9. What is the difference between a...

8. Why choose stratified sampling? Mention two main reasons.

9. What is the difference between a “random” (probability) sample and a nonrandom sample?

Expert Solution

A sample is any number of individuals taken from the population for the purpose of research analysis. A sample is considered to be the true representation of a population. There are different methods of collecting a sample. The two methods are; Probability Sampling and Non-Probability Sampling.

Probability Sampling is when every individual has equal, probable chances of being selected in the sample. Non-Probability Sampling on the other hand, provides no accurate basis of including individuals in a sample and them being the true representation of the population. The whole idea behind sampling is to extract a smaller amount of individuals from a worldwide population while still representing the population.

Stratified sampling method is a form of sampling wherein the researcher equally or proportionally divides the sample in different subgroups or strata. For instance, a researcher wants to study the effect of work pressure on depression. His total sample is 500. In a stratified sample he would randomly choose 500 people, however, divide them equally in two groups of 250 males and 250 females.

The advantages of stratified sampling are; it is the most accurate representation of the population within the strata or subgroups. The results of the study are more reliable and valid in comparison to other sampling methods.

Hayet Jeridi answered 4 weeks ago

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