Probability Sampling

Probability sampling involves the random selection of elements from the population.

Probability samples involve selecting units at random, some confidence can be placed in their representativeness.

The four most commonly used probability sampling designs are:

1. simple random

2. stratified random

3. cluster

4. systematic sampling1. Simple Random Sampling

Simple random sampling is the most basic probability sampling design. Becausemore complex probability sampling designs incorporate features of simple random sampling, the procedures are briefly described so that you can understand what is involved.

Simple random sampling is a laborious process. The development of the sampling frame, enumeration of the elements, and selection of the sample are time consuming steps, particularly with a large population. Moreover, it is rarely possible to get a complete listing of population elements; hence, other methods are often used.

Example of a random sample

There are 30 students on your population, out of it, you want to get a sample of 10.

So, number each of them from 1 to 30 and randomly choose 10.

How? Put numbers 1-30 in a box or hat and then pick 10.

2. Stratified Random Sampling

In stratified random sampling, the population is divided into homogeneous subsets from which elements are selected at random. As in quota sampling, the aim of stratified sampling is to enhance the samples representativeness. The most common procedure for drawing a stratified random sample is to group together those elements that belong to a stratum and to randomly select the desired number of elements.

Example of a stratified random sample

In a school of 200 students, you want to sample 40 students and want all grades to be appropriately represented. How should you ask in each year?

Year frequency

1st30

2nd40

3rd50

4th80