Important Notes:
1. Do not include spaces or symbols (such as parentheses、commas, etc.) in dataset variable names.
2. Supports datasets in various formats under 10 MB.
3. Before importing data, it is recommended to read the introduction about dataset formats.
表格内容：
I. Basic Information
This platform supports data import in CSV, Excel, and RDS formats, including common SPSS software formats and SAS data formats. The maximum dataset size should not exceed 10 MB.
Excel format datasets can be either self-created or exported from SPSS.
CSV format can generally be exported from Excel or SPSS.
For beginners, it is recommended to export from SPSS, as SPSS has a fixed dataset format while Excel does not.
Dataset Format Requirements
Whether in CSV or Excel format, the basic structure remains the same!
The first row should contain variable names, preferably in English or pinyin. Chinese characters are not recommended, and special symbols such as parentheses ( , asterisks *, percent signs %, etc., should be avoided.
Starting from the second row, each row represents all variable information for a single research subject.
Each column represents the values of a single variable for all subjects.
It is generally advised to use numerical values for variables in CSV and Excel files. For example, male = 1, female = 2; blood type (1, 2, 3, 4). This approach is flexible and ensures compatibility across various statistical software. If there is uncertainty about dataset value assignments, please provide a variable codebook.
By default, missing values should be left blank. Do not use “NA” or other placeholders.
Unless dealing with specific strings (e.g., names), avoid using Chinese characters or English strings as variable values in the dataset, as this may cause issues in subsequent analyses.
How to Organize a Standardized Dataset
If you are an expert in data analysis, feel free to use your own methods for data organization. However, I strongly recommend that beginners import raw datasets into SPSS for data management.
The advantages of using SPSS for data organization are:
It features a fixed dataset structure and provides standardized computation and transformation functions, which are sufficient for beginners’ needs.
Unlike Excel, it prevents accidental and unnoticed modifications to data values.
(While I occasionally use Excel for adjustments when necessary.)
Remember: Variable values in SPSS datasets should generally be assigned using numerical codes.
Batch Difference Analysis by Group
1 Analysis Results
2 Statistical Analysis Methods
3 Results Description
4 Description Example (English)
Batch Difference Analysis for Quantitative Data
1 Analysis Results
2 Statistical Analysis Methods
3 Results Description
4 Description Example (English)
