OLS Regression Skill

This skill provides comprehensive guidance for OLS regression and linear models in empirical research. It covers model specification, assumption testing, diagnostic checks, and result interpretation, with code examples in Python, R, and Stata.

Core Workflow

When assisting with OLS regression, follow this sequence:

1. Clarify the research question and data — understand dependent variable, key regressors, and sample
2. Specify the model — choose functional form, control variables, fixed effects if needed
3. Run the regression — provide code in the user's preferred language
4. Check assumptions — run diagnostics systematically (see references)
5. Interpret and report — explain coefficients, significance, fit, and caveats

Key Concepts