Studying Sociology GCSE and Sociology A Level 4: Sampling Methods in Sociology – Random (Probability) Sampling
Here is the fourth in our series of study blogs for those studying A level Sociology and GCSE Sociology.
Sampling Methods in Sociology – Random (Probability) Sampling
As we said in our second blog, it is often impossible to test the whole population you want to study, so sociologists will choose a small group of individuals to study. This small group is known as a sample. So how do sociologists choose their sample groups? There are two main types of sampling – Random (Probability) sampling and Non-Probability Sampling. We will talk about Random sampling in this blog and Non-Probability Sampling in the next blog.
Random (probability) sampling
- Random sampling uses probability. So if we have 1000 people we wish to study, but we can only study 100 people, we might choose 100 names randomly out of a hat, so each person has an equal chance, or probability, of being chosen. As they are selected randomly, it is more likely that the participants are representative of the population as a whole. Examples of Random Sampling include:
- Systematic Sampling – This includes choosing a starting point in the sampling frame. For example, you may decide to choose every 7th person on a list. There can be a bias with this though as is there is an underlying pattern with the sampling frame.
- Stratified Random Sampling – With this form of sampling, the population is put into “strata”. A strata is like a segment of the population. The strata can be based on gender, age, income and so on. You have probably seen questionnaires where you are asked to tick your age: 0 – 18 years 19 – 24 years 25 – 34 years, and so on. The participants are then selected randomly from each segment. So if you wanted 20 participants from each age group, you would randomly select 20 0 – 18 year olds, 20 19 – 24 year olds, and so on.
- Simple Random Sampling – Each member of a population has an equal chance of being selected to be in the sample.
See the next blog for information on non-probability sampling.