A codebook documents a dataset’s variables, coding schemes, methodology, and usage information. It helps analysts understand how a resource was developed and use it responsibly. section 10.3.3
A codebook commonly records:
- Dataset characteristics, including missing-value codes, sample size, and sampling strategies. section 10.3.3
- Variable names, detailed descriptions, survey questions, and supported data types such as choices, integers, and Boolean values. section 10.3.3
- Caveats and limitations that may affect result quality, including missing values. section 10.3.3
- Summary statistics for questions, which can support part of exploratory analysis. section 10.3.3
Matching survey topics to dataset columns
The University of Michigan’s Monitoring the Future survey provides a codebook with extensive methodology and data descriptions. Searching it helps match topics of interest to dataset column names before analysis. section 10.3.3

