Stata® 101 – Introduction to Data Management, Analysis, and Visualization

LecturerProf. Dr. Peter Schäfer
TU Dresden (Chair of Business Administration, esp. Management Accounting and Control)
Room/AddressTU Dresden, Faculty of Business and Economics
Georg Schumann-Bau (SCH/B37)
Seminar content
  • You will get a short introduction to Stata basics, including the user interface, the do-file editor, the syntax, and the help system.
  • You will learn how to manage your data in Stata (e.g., importing and exporting data from different formats, matching and merging datasets, reshaping and collapsing data, generating variables, and handling duplicates)
  • You will learn how to produce a workflow that helps to reproduce your work and document it for your publications. This part includes understanding how to use Stata programming (e.g., using macros, branching, looping, assessing saved estimation results, user-written commands, and ado-files) to improve your work in Stata. You will also learn how to get help from the Stata community and get a first idea of how to create your own commands.
  • You will understand how statistical models are estimated in Stata and get an overview of some estimation commands available.
  • You will learn how to export nice tables presenting your estimation results and visualize your data and results with graphics. You will learn the syntax of different graph types, how to format them, and how to export them to your manuscripts.
  • You will need a laptop with access to Stata software.
  • Course material and readings will follow.
CertificateDoctoral candidates from the Faculty of Business and Economics, TU Dresden can earn a certificate according to § 9 of the Ph.D. doctoral regulations (PromO 2018):
Doctoral candidates of Business Administration: § 9 (1) Nr. 5 or 6
Doctoral candidates of Business Information Systems: § 9 (1) Nr. 6
Doctoral candidates of Economics: § 9 (1) Nr. 6

Doctoral candidates from other universities can earn a certificate as well.
  • Participation in all seminar sessions is mandatory.
  • Part of the course is replicating an existing paper’s results. You will get the data and submit your code, result tables, and figures.
RegistrationParticipation is limited (max. 15). The registration deadline is 31.07.2024.
To register, send an e-mail to Dr. Uta Schwarz: