Commonly used simple random sampling methods are

① Simple random sampling, ② systematic sampling, ③ stratified sampling and ④ cluster sampling method.

For example:

Simple random sampling: This method is commonly known as random sampling method. The reason why it is called simple random sampling method means that every individual in the group has the same chance to be drawn. In order to realize the randomization of sampling, we can draw lots (or draw lots), look up a random number table, or roll dice.

For example, 10 products are randomly selected from 100 products, and these 100 products can be numbered from 1 to 100, and then 10 is randomly selected by lottery (or lottery). If the number drawn is 10, such as 3,7, 15,18,23,35,46,51,72,89, etc. , and then take out the products with the number of 10 to form a sample, which is a simple random sampling method.

Systematic sampling method: systematic sampling method is also called equidistant sampling method or mechanical sampling method. For example, to extract 10 products from 100 products, first number 1 00 products in the order of1,2, 3, …, 100; Then determine which product of 1- 10 is selected as the sample by drawing lots or looking up the random number table (assuming No.3 here);

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In addition, the product numbers of other selected samples are: 13, 23, 33, 43, 53, 63, 73, 83 and 93; Finally, the sample consists of 10 products numbered 03, 13, 23, 33, 43, 53, 63, 73, 83 and 93. Because the systematic sampling method is simple in operation and not easy to make mistakes in execution, people are happy to use it in the production site.

Stratified sampling method: stratified sampling method is also called type sampling method. It is a method of randomly selecting samples (individuals) of different layers from the whole that can be divided into different subgroups (or layers) according to the specified proportion.

Using stratified sampling method, five parts are randomly selected from three places where the parts are stacked, which together form a sample of *** 15 parts. The advantage of this sampling method is that the sample is representative and the sampling error is small. The disadvantage is that the sampling procedure is simpler and more complicated than random sampling. Cluster sampling method: In cluster sampling method, the population is divided into many groups, and each group is composed of individuals in a certain way. Then randomly select several groups, and the sample consists of all individuals in these groups. The background of this sampling method is that sometimes for the convenience of implementation,

The disadvantage is that the sample only comes from minority groups, and it is unevenly distributed in the whole population, with poor representativeness and large sampling error. This method is often used in process control. Here is an example to illustrate the application of these four sampling methods. [1] Suppose that a finished part is packed in 20 parts boxes, each containing 50 pieces, and the total * * * is 1000 pieces.

If you want to take 100 parts as samples for testing and research, how should you use the above four sampling methods? ① Pour 20 boxes of parts together, mix them evenly, number the parts from 1 to 1000 one by one, and then extract 100 samples with irregular numbers by looking up the random number table or drawing lots. This is a simple random sampling.

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② Pour 20 boxes of parts together and mix them evenly, and number them one by one from 1 to 1000. Then, the starting number is determined by looking up the random number table or drawing lots, such as 16, and then the part numbers of the samples are selected as 26, 36, 46, 56, ..., 906, 965438.

(3) For all 20 boxes of parts, 5 pieces are randomly selected from each box, and *** 100 pieces form a sample, which is stratified sampling. (4) First, two boxes are randomly selected from 20 boxes of parts, and then all the two boxes of parts are inspected, that is, the two boxes of parts are regarded as "clusters" and they form samples, which is cluster sampling.