Questionnaire survey is divided into two categories: scale questionnaire and non-scale questionnaire.

Scale questionnaire is usually used in academic research, which is characterized by more cognitive items of attitude, reflecting the attitude, views and attitudes of the sample population towards something. By studying the relationship between research variables, we can find out the logical relationship between them.

No-list questionnaire more reflects the fact and basic attitude of the respondents to a certain status quo, such as the sample of online shopping reasons, no.

The reasons for online shopping, the use of online shopping platforms, etc. This kind of questionnaire is more about the logic of analytical thinking, the understanding and analysis of the present situation, and the basic attitude towards the sample.

Second, the analysis method

From the analysis method, the biggest feature of the scale questionnaire is that there are many scale questions, which correspond to' variables' or' dimensions'. It is convenient to study the relationship between' variables'. And methods such as reliability, validity and factor analysis can be used.

The biggest feature of scale-free questions is that most of them are multiple-choice questions, multiple-choice questions or sort-fill-in-the-blank questions, and there are few scale questions (but scale questions refer to questions with similar answers, such as "very different opinions", "relatively different opinions", "neutral opinions", "relatively agreed opinions" and "very agreed opinions"). Basic frequency analysis and cross analysis are mostly used, and charts are used for diversified display.

Third, the analysis results

Questionnaire data can generally be analyzed by SPSS. If the analysis foundation is weak, SPSSAU can be used for analysis. The analysis results will generate a "three-line table" format, and the system will automatically generate an indicator interpretation report.

Intelligent analysis

Fourth, write a research report

According to the order of questionnaire analysis, the analysis results are written into logical reports, and meaningful and valuable suggestions and measures are put forward on the basis of the conclusions.

Regarding the writing of data report, from the point of view of data analysis alone, it is suggested to proceed from actual needs, such as studying the relationship between differences, so it is necessary to know whether there are differences first, then there are differences, and what are the specific differences. When there are differences or no differences, what should be the corresponding suggested measures? According to this idea, I believe it is not difficult to write a data research report.