How to organize lottery activities

Data analysis is an important work, and sampling is the basis of data analysis. This paper will introduce four common sampling methods to help readers better master the skills of data analysis.

simplerandom sampling

Simple random sampling is like playing a lottery game, and every partner has an equal chance to be selected. Although the operation is simple and easy, you may feel a little confused when you meet a large group of people.

systematic sampling

Systematic sampling is to number each small partner and then select them according to certain rules (for example, every five). Although the operation is simple, it may be a little biased if there is a change in the overall situation.

Nested sampling method

Cluster sampling is to divide everyone into several groups and then randomly select several groups to represent them. This is convenient to organize and low cost, but it may not be as accurate as random sampling.

group sampling

Stratified sampling is to divide everyone into several layers according to certain characteristics, and then randomly select from each layer. The selected samples are more representative and the error is smaller.

Multistage sampling

In practice, we often combine these methods to construct multi-stage sampling like building blocks to make the data more convincing!