1, simple random sampling
Simple random sampling is the most basic and widely used sampling method. Generally speaking, each individual has the same chance of being drawn, which can be achieved by drawing lots, random number tables or lottery machines. For example, randomly select samples from the population, each individual number, and randomly select individuals with specific numbers as samples.
2, the system random sampling
Systematic random sampling, also known as equidistant sampling or mechanical sampling, arranges numbers according to the order of individuals in the group and samples at fixed intervals. Firstly, the number of the first sample is randomly determined, and then one sample is selected every n samples according to the ratio of the sample to the population.
For example, take 100 students out of 800 students as subjects, calculate the number of sampling intervals according to the formula, and then randomly select a number from 1-8, assuming it is 6, then the number is 6, 14, 22, 30, 38, 46...798.
3. Stratified random sampling
Stratified random sampling, also known as classified sampling or quota sampling, divides the population into several levels or categories (sub-populations) according to certain standards, and then randomly selects samples according to the proportion of each level or category in the population.
For example, the study attitude of 800 students in a school was investigated, and two-tenths of the students (160) were selected as samples. Firstly, according to the evaluation criteria, students are divided into four levels: excellent, good, medium and poor, and then samples are taken proportionally from these four levels through simple random sampling.
4. Cluster random sampling
Cluster random sampling takes natural groups (schools, classes, etc. ) as a unit, and randomly select samples from a larger population.
For example, a first-year student in a certain district did a study and randomly selected several schools. In the first grade of these schools, two classes were randomly selected as samples, and all the individuals in the classes were subjects. Cluster random sampling is convenient and feasible, which will not disturb the original class because of research, and can give consideration to the regular teaching order and will not affect the cooperation between teachers and students.
These sampling methods have their uses and advantages in different situations, and choosing the appropriate sampling method depends on the purpose and overall characteristics of the study.