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Data dictionary

As explained in Effective Data Analysis

A data dictionary is documentation that defines a dataset’s fields, data types, valid response options, and related descriptive information.

A data dictionary defines a dataset’s coded fields, data types, valid response options, and related descriptive information. It makes large survey files interpretable before analysis. section 10.3.2

Use a data dictionary to:

  • Decode dozens of abbreviated or coded column names. section 10.3.2
  • Identify each field’s data type and available response options. section 10.3.2
  • Assess how common each response was through reported response percentages. section 10.3.2

Survey analysis

An analyst comparing Pacific and Northeast populations with General Social Survey data can use the data dictionary to interpret demographic and opinion variables before testing regional differences. section 10.3.2

How Effective Data Analysis covers it

How deep it goes
Defines fields, types, responses, and response percentages but does not provide a detailed analysis workflow.
Examples
Uses General Social Survey and Monitoring the Future files distributed as CSV, STATA, or SPSS-compatible datasets.
What it assumes
Assumes access to a downloaded survey dataset and teaches the metadata needed to read its coded columns.
What you can do after
Evaluate/understand survey variables well enough to compare populations and investigate differences in important characteristics.
How it connects
Connects coded column names with data types, response options, survey datasets, and population comparisons.

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