What are the analysis methods of questionnaire data?

First of all, it is not difficult to learn to do basic data analysis, and you can get started quickly by mastering some necessary knowledge. The path of learning data analysis is as follows: data type identification, research method selection and result analysis.

Identification of (1) data type

Data type is the cornerstone of all research, and it is also the most basic and critical thinking in data research. After confirming the authenticity and accuracy of data, that is, after data cleaning, data types can be distinguished. All data can be divided into two types, including qualitative data and quantitative data.

Quantization: Numbers have comparative significance. For example, the greater the number, the higher the satisfaction, and the scale is a typical quantitative data.

Classification: Numbers have no comparative significance, such as gender, 1 for men and 2 for women.

(2) Selection of research methods

After the data type is determined, the choice of data analysis method can be understood at this time. For example, when designing SPSSAU, it distinguishes data types and the relationship between X and Y, such as gender and smoking, where X is gender and Y is smoking. X and y are classified data. At this time, you should choose "cross-chi-square" analysis.

The first step is to choose the correct research method, that is, the identification of data types.

The second step is to analyze the research purpose. Common research purposes include: the basic description of data, the study of influence relationship, the study of difference relationship and other relationships.

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(3) Analysis results

The analysis foundation is weak, so it can be analyzed by SPSSAU, and the system will automatically generate an index interpretation report.

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Second, the analysis of ideas template

The research framework is the core of analysis, which can be generally divided into dimensionless table and scale questionnaire, and then analyzed against the framework.

The biggest feature of scale questionnaire is that there are many scale questions, and the scale questions 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.