In order to do estimations on the whole population, it is required to create samples that can represent the population. There are different sampling techniques that achieve this goal, where all of them have different advantages, flaws and objectives. It is good to be able to know the difference between each one of them.

**Convenience sampling** the sampling done on the easiest available members of the population.

e.g. if you wanted to do a survey on students in your school, you would ask students you are personally familiar with.

**Simple random sampling** the sampling where each member of the population has an equal chance of being selected.

e.g. you could randomly put all students’ names in a hat and randomly select sample members out of it.

**Systematic sampling** the sampling where the population is arranged or listed in a specific order and then elements from that list are selected at fixed intervals starting at a random point.

e.g. all student names could be written in an alphabetical list and every 10th student is chosen.

**Stratified sampling** the population is split into several smaller groups, known as “strata”. Then a random sample is selected from each strata.

e.g. students could be split according to their age groups, so that randomly several students from each age group are taken into a sample.

**Quota sampling** similarly to stratified sampling the population is split into groups. However, sampling from each group is done in a non-random manner. E.g. sampling could be done in proportion to the size of each strata.

e.g. if the students are split into females and males with ratio 70% to 30%, then your sample should contain about 70% females and 30% males.