1, random sampling:
Random sampling requires strict compliance with the principle of probability, and each sampling unit has the same probability of being drawn and can be reproduced. Random sampling is often used when the population is small, and its main feature is to extract from the population one by one. Random sampling can be divided into simple random sampling, systematic sampling, stratified sampling and cluster sampling.
2, stratified sampling:
Stratified sampling refers to dividing the population into disjoint parts when sampling. [2]? Then according to a certain proportion, a certain number of individuals are independently extracted from each layer, and the individuals taken from each layer are combined as samples. The smaller the intra-layer change, the better, and the greater the inter-layer change, the better.
3. Cluster sampling:
Cluster sampling, also known as cluster sampling, is to merge all units in a group into several sets that do not cross and repeat each other, which are called groups; A sampling method in which samples are sampled in groups. When cluster sampling is applied, each cluster is required to have good representativeness, that is, the differences between units within the cluster are large and the differences between groups are small.
Extended data:
1, advantages and disadvantages of random sampling:
(1) Advantages: simple operation;
(2) Disadvantages: The overall scale is too large to be realized.
2. Advantages of stratified sampling:
(1) reduces the sampling error, and increases the uniformity in the stratified layer, thus reducing the variability of observation values and the sampling error of each layer. With the same sample content, the total standard error of stratified sampling is generally less than that of simple random sampling, systematic sampling and cluster sampling.
(2) The sampling method is flexible, and different sampling methods can be adopted for different layers according to the specific conditions of each layer. For example, the prevalence of a disease among residents in a certain place can be divided into two levels: urban and rural. Urban population is concentrated. Systematic sampling method can be considered; The rural population is scattered, and the cluster sampling method can be used.
(3) Different levels can be analyzed independently. The disadvantage of stratified sampling is that if the stratified variables are not selected properly, the intra-layer variation is large and the inter-layer mean value is similar, stratified sampling will lose its significance.
3. Advantages and disadvantages of cluster sampling.
The advantages of cluster sampling are convenient implementation and saving money;
The disadvantage of cluster sampling is that the sampling error caused by large differences between different groups is often greater than that caused by simple random sampling.
References:
Baidu encyclopedia-sampling method