First, simple random sampling
Methods: Draw lots, random number table.
Conditions of use: the number of samples is small and the overall heterogeneity is small.
Advantages: simple, easy to operate, convenient for error calculation and strong representativeness.
Disadvantages: when the sample size is small, there may be deviations, which will affect the representativeness of the sample.
Second, systematic random sampling.
Methods: equidistant sampling
Conditions of use: suitable for large samples
Advantages: strong representativeness, more accuracy, scattered sampling and systematization.
Disadvantages: If the population changes periodically, the error will increase.
Third, stratified random sampling method
Methods: Samples of different levels were selected in different layers according to the proportion.
Conditions of use: the overall composition is mixed, with great differences between layers.
Advantages: reduce errors, effectively control, and adopt different sampling methods and proportions for each layer according to specific conditions, which is more flexible.
Disadvantages: it is difficult to scientifically analyze and grasp the division of each layer.
Fourth, overall random sampling.
Methods: The whole population was regarded as individuals.
Conditions of use: large overall scope and large quantity.
Advantages: simple sampling, saving time and labor.
Disadvantages: low representativeness, not suitable for low homogeneity of each layer.