What is Random Sampling?
A subset of a statistical population in which each member of the subset has an equal probability of being chosen. A simple random sample is meant to be an unbiased representation of a group.
Different Types of sampling:
Systematic Sampling
A systematic sample is a type of sampling where you take samples depending on a fixed rule. For e.g. on a production line, to make sure the product is good enough to pass through and be sold, someone might take every 50th item and make sure it is suitable and nothing has gone wrong, because if there is something wrong, they will need to check all the ones after that.
Stratified Sampling
Stratified sampling is when you divide a group into categories and then take a random sample from each of those groups. For e.g. you have four nationalities English, Australian, German and French. Australia has 190 people, England has 50, Germany has 150 and France has 10, you would take a random group of people from each nationality and ask them questions. However, the groups that you take have to have the same number of people in them.
Quota Sampling
Quota sampling is like stratified sampling but you can the groups you take don’t have to have the same number of people in them. For e.g. if you have the same number of people and the same nationalities, but you take 80 German people, 2 French, 180 Australian and 20 English and then asked them do you like vegemite, it would yield a very bias result because most Australians will say they do, but the other nationalities will say no, meaning that it was rigged in Australia's favour.
Cluster Sampling
Cluster sampling is a method in which groups (clusters) of sampling units (and not individual units) are selected from a population for analysis. For e.g. if you want to survey people in 3 hotels, instead of surveying everyone in the three hotels, you choose one at random and survey the people in that hotel on their stay.