What is Sampling?
Suppose that you would like to know the average height of the human population. It is impossible to know this because you cannot know the height of every living human being and therefore you cannot calculate its mean. Click here to see the Average Human Height Worldwide. How is it possible to know this information?
Instead of measuring the height of every human being, we measure the height of a sample taken from that country. If the sample is chosen well, the sample represents the entire population well. Any statistics calculated from a good sample can be used to describe the whole population. This is called inference.
For a sample to be useful it must be:
- unbiased – if we are interested in the distribution of height, our sample should not be restricted to basketball players, for example.
- representative size – a sample of two is not sufficient to give an accurate representation of a large population as it is prone to anomalous skewing.
Methods of Sampling
Simple Random Sampling
Simple random sampling is a sample selection process whereby each member of the population has an EQUAL chance of being selected.
Example – A company has 50 employees. The company would like to know if the employees are happy with the restaurant facilities. A sample of 10 employees will be questioned to find out their views. To select this sample of 10, 50 balls labelled with staff numbers are put into a bag, shaken and 10 removed without replacement. This is an example of simple random sampling. Every combination of 10 balls is equally likely.
The sampling frame is the list of employee numbers.
Note that the sampling frame is a list of all members of a population. Quite often, the biggest problem with simple random sampling is having a complete and accurate sampling frame.
Stratum is another words for class, level or grade. Strata is then the plural of stratum. Stratified sampling is a sampling technique that preserves the given strata proportions.
Example – There are 400 students on the Mathematics programme at a University. 34% of these students identify as female. A sample of 50 students is chosen to find out how many extra reading hours the students complete. 17 students of those sampled identify as female in a stratified sample – this is 34% of 50.
a sampling technique where the sampling starting point is chosen randomly and the rest of the sample is chosen periodically thereafter.
similar to stratified sampling but researchers may select the units they require from the given strata.
or convenience sampling, is obtained when members from a given population are willing to participate in the investigation, such as a survey.
Once you have taken a sample from a given population, you would then analyse that data you have collected and gather statistics. How you present data and interpret your findings is very important – see Data Representation & Interpretation.