Sampling is key when studying a large population. The true art is to increase your generalisability. Depending on your sampling size, depends on how this is achieved. Sampling techniques falls into two categories:
Non representative sampling.
Random sampling. Random sampling is simple. It is random. If you put 100 names into a hat and draw ten. Each person in that hat has an equal chance of being chosen.
Systematic random sampling. There are two stages to this research method. 1) Place the names into some sort of order. This can be anything from oldest to youngest to gender or alphabetical order. 2) Choose the nth number form the list. E.g. I choose every 10th person, or every 3rd person
Stratified random sampling. This is where, again, participants are placed into groups. So, if a researcher was investigating age and gender in a high school, the researcher would choose 10 males and 10 females from each year 7-11 to generate his sample size.
Quota sampling. Quota sampling means to take a very tailored sample that’s in proportion to some characteristic or trait of a population. For example, you could divide a population by their age, how much they earn, their ethnicity etc. The population is divided into groups and samples are taken from these groups making sure that the correct proportions are representative of the population e.g. if your population sample is 25% African, you make sure your sample size is. It is considered to be a non-probability sampling technique.
Snowball sampling. Snowball sampling is using a target and then using their friends and their friends etc to generate your population sample.
Opportunity sampling. This is simple, if you stand in a street, whoever you find is the target.