1, simple random sampling (simple random sampling)
Simple random sampling is one of the most basic sampling methods. In this sampling method, the probability of each individual being selected into the sample is equal, and the samples are independent of each other. Simple random sampling can be done by random number generator or lottery.
2. Systematic sampling.
Systematic sampling is a method of regularly selecting samples from the population. For example, choose a starting point in the population, and then choose one at regular intervals, such as every five people, until the required sample size is reached. This method is more efficient than simple random sampling, but it requires a certain order of the population.
3, stratified sampling (stratified sampling)
Stratified sampling is to divide the population into several layers with similar characteristics (called stratification), and then randomly sample from each layer. This can ensure that the samples are representative at all levels and fully consider the differences between different levels.
4, Cluster Sampling (cluster sampling)
Cluster sampling is to divide the population into several non-overlapping small groups (called groups), and then randomly select some of them and take all the individuals in the group as samples. This method can be used to reduce the cost of investigation, especially when the individuals in the group are similar.
5. Convenient sampling (coincidence sampling)
Convenient sampling is a method to select samples according to the convenience and ease of researchers. This sampling method can't guarantee the representativeness and statistical generalization of the samples, and it is only suitable for the occasions of preliminary exploration or informal research.
6, effect sampling (Purposive Sampling)
Effect sampling is a method to select samples purposefully according to the research purpose and specific needs. According to the characteristics and objectives of the research problem, we can set the criteria for selecting samples, so that we can deeply understand a specific field or a specific population.
7. Fixed sampling
Quota sampling is to select samples from different subgroups according to predetermined quotas or standards to ensure that the samples are representative in each subgroup. Similar to stratified sampling, the difference is that quota sampling is not random sampling, but sampling according to pre-set quota requirements.