HUNTERTUTORING

Stata

Graduate · CS / Programming

Syllabus focus

Topics typically covered

Standard syllabus

Stata fundamentals

  • Do-files, logs, and reproducible workflows
  • Importing Excel, CSV, and survey formats
  • Variable types, labels, and value labels
  • generate, replace, egen, and recode
  • merge, append, and reshape (wide/long)

Analysis commands

  • Descriptive statistics and tables
  • Graphs: histogram, scatter, regression fit
  • OLS regression: reg, margins, and predictions
  • Hypothesis tests and confidence intervals
  • Panel data: fixed and random effects (intro)

Stata workflow

  • Do-files, logs, and reproducible projects
  • Data cleaning: reshape, encode, and missing values
  • by-group processing and egen
  • Estimation commands and stored results
  • Postestimation and diagnostics
  • Graphics for exploratory and publication plots

STEM / applied

Applied econometrics

  • Instrumental variables and 2SLS (intro)
  • Difference-in-differences and event studies (intro)
  • Logit/probit for binary outcomes
  • Survey weights and svy commands (intro)
  • Exporting tables for publication (esttab/outreg)

Data engineering in Stata

  • Loops, macros, and programmable workflows
  • Mata matrix programming (intro)
  • Cleaning messy administrative data
  • Replicating published tables from raw data
  • Integrating Stata output with LaTeX/Word reports

Empirical research support

  • Survey weights and complex samples (intro)
  • Panel data tools survey
  • Exporting tables for papers (esttab/outreg survey)
  • Merging administrative datasets carefully
  • Interpreting coefficients for stakeholders
  • Capstone: replication-style analysis with do-file package

Notes

Common in economics, policy, and public health programs. Command syntax is Stata-specific.