Sampling survey is a commonly used data collection method, and its basic idea is to infer the characteristics of the population by extracting some samples from the population. In the process of sampling, we need to follow some sampling principles to ensure that the sample can represent the whole population, reduce sampling errors and improve the accuracy of inference.
Second,
Sampling principles include the following:
1. Randomness: Samples need to be randomly selected from the population to ensure that each individual has an equal chance to be selected.
2. representativeness: the sample needs to be able to represent the overall characteristics, such as population age, gender, region, etc.
3. Independence: The samples need to be independent of each other, and the selection of each sample is not affected by other samples.
4. Feasibility: The samples need to be easy to obtain and operate.
Third,
Analogical reasoning is a commonly used reasoning method. By comparing and analogizing known situations and questions, the answers to unknown situations and questions are inferred.
In short, the sampling survey should follow certain sampling principles to ensure the representativeness and independence of the samples. At the same time, data analysis methods, such as analogical reasoning, should be used reasonably to infer the overall characteristics and conduct accurate data analysis.