(1) Simple random sampling:
Simple random sampling means that the sampling process should be carried out independently, and the chances of each individual being drawn in the population are equal. Random sampling is not random sampling, and random sampling is easily influenced by personal likes and dislikes. In order to achieve randomization, we can draw lots, roll dice or look up a random number table.
If l0 products are randomly selected from 100 products to form a sample, the 100 products can be numbered from L to 100, and then l0 numbers are randomly selected by drawing lots, and the products represented by these l0 numbers form a sample. The advantages of this sampling method are small sampling error and complicated procedure. In practice, it is not easy to truly achieve equal opportunities for each individual to be drawn.
(2) Periodic systematic sampling:
Periodic systematic sampling, also known as equidistant sampling or mechanical sampling, is to sequentially number the population, determine the first block by drawing lots or looking up a random number table, and then take samples in turn according to the principle of equidistant sampling. If five samples are taken from 120 parts, the products are numbered according to the production order, the first part is determined by simple random sampling method, and then 1 part is taken every 24 numbers (from 120÷5=24), and five samples are taken by * *.
This method is especially suitable for online sampling, simple and easy to operate, and it is not easy to make mistakes in implementation. But once the starting point of sampling is determined, the whole sample is completely fixed. There is a certain periodic change in the overall quality characteristics. When the sampling interval coincides with the change period of the quality characteristics, samples with large deviation may be obtained.
(3) stratified sampling method:
Stratified sampling method, that is, individuals at different levels are randomly selected from a population that can be divided into different subgroups according to the prescribed proportion.
When the same product is produced by different equipment and different environments, the quality of the product may vary greatly due to different conditions. In order to make the sampled samples representative, the products produced under different conditions can be grouped to make the products in the same group have the same quality, and then the samples in each group are randomly selected in proportion to synthesize a sample. The samples obtained by this sampling method are representative and the sampling error is small. The disadvantage is that the sampling procedure is complex and is usually used for product quality inspection.
(4) cluster sampling method:
In this method, the population is divided into several groups in a certain way, and then several groups are randomly selected, and the samples are composed of all individuals in these groups. For example, according to the production process, 1000 parts are put into 20 boxes with 50 parts in each box, and then a box is randomly selected, and 50 parts in this box form a sample. This sampling method is convenient to implement, but the samples come from individual groups and cannot be evenly distributed in the population, with poor representativeness and large sampling error.