Introduction to Stata - JEM237

• Title: Introduction to Stata
• Czech title: Introduction to Stata
• Form of teaching: lecture+practicals
• Guaranteed by: Institute of Economic Studies (23-IES)
• Faculty: Faculty of Social Sciences
• Actual: from 2026
• Duration in semesters: 1
• Semester: winter
• E-Credits: 3
• Examination process: winter s.:
• Hours per week, examination: winter s.:4/4, C [HS]
• Capacity: unknown / unknown (20)
• Maximum number of enrolled students: 20
• Min. number of students: unlimited
• 4EU+: no
• Virtual mobility / capacity: no
• State of the course: taught
• Language: English
• Teaching methods: full-time
• Repeated enrollment: 2 / 2 / 1 / 2
• Note: course can be enrolled in outside the study plan; enabled for web enrollment; priority enrollment if the course is part of the study plan
• Guarantor: Mgr. Barbara Pertold-Gebicka, M.A., Ph.D.
• Teacher(s): Matěj Bajgar, D.Phil.; Mgr. Barbara Pertold-Gebicka, M.A., Ph.D.

Descriptors

This intensive four-day course introduces master’s and PhD students to data manipulation and econometric analysis using Stata. Participants will learn how to manage data, implement core econometric methods, interpret and export results, and effectively use Stata help resources, online forums, and AI tools to develop and refine their code. The course is designed to prepare students to write their thesis using Stata or to work as research assistants in empirical economics.

Last update: Pertold-Gebicka Barbara, Mgr., M.A., Ph.D. (25.05.2026)

Course completion requirements

To pass the course, a student has to complete 3 practical home assignments after the first, second, and third day of the course.

Last update: Pertold-Gebicka Barbara, Mgr., M.A., Ph.D. (25.05.2026)

Syllabus

All sessions are taught in room 016 (the computer lab).

Day 1 (September 21, 2026, 2pm-5pm): Introduction to Stata and Data Management

Stata interface and workflow: commands, syntax, and operators — Using help files and online resources — How Stata structures data (observations and variables) — Loading and examining data — Basic data management (sorting, filtering, generating variables, handling missing values)

Day 2 (September 22, 2026, 2pm-5pm): Building and Managing an Analysis Dataset
Workflow: constructing an analysis dataset from raw data — Using do-files and structuring reproducible code — Data cleaning and transformations — Combining datasets (merge, append) — Consistency checks and common data issues — Descriptive statistics and tabulations  —   Common pitfalls.

Day 3 (September 23, 2026, 2pm-5pm): Descriptive Analysis, Graphs, and Programming Basics
Analyzing data using graphs and tables —  Analyzing data using regressions  — Exporting tables and outputs —   Creating and customizing visualizations  — Introduction to Stata programming (loops, locals/globals, return lists)

Day 4 (September 24, 2026, 2pm-5pm): Econometric Analysis and Research Workflow
Advanced regression analysis ins Stata — Interpreting and presenting results — Debugging and troubleshooting code — Using Stata help, forums, and AI tools for code development — Introduction to survey data (clustering, stratification, weights)

Last update: Pertold-Gebicka Barbara, Mgr., M.A., Ph.D. (25.05.2026)