Workshop: Stata (Basic)

The Stata statistical software is increasingly popular among social scientists because it combines the advantages of commercial and free-licensed software. This makes it a perfect tool for research purposes. Yet Stata is not featured as prominently in the curricula of German-speaking universities as it should be. This workshop aims to fill this gap, providing participants with the basic skills to apply Stata individually using specialized methods.

Target Group

Scientists from different disciplines who have a basic knowledge of statistical methods used in empirical social research and who are starting with Stata as their first statistical software or are switching from another software.

Goals

This workshop is designed to enable participants to conduct and document their own basic statistical analyses using Stata. They will learn how to handle the software and how to use Stata’s basic programming language. The functions and procedures of data management and data analysis will be explained in detail and with the help of practical, interactive exercises. We will use example datasets, but participants will also have the opportunity to work on their own data.

Content

• introduction to the basic features of Stata
• help functions and web resources
• data management (import/export of data, recoding, missing values, labels)
• by-prefix, system variables _n and _N
• documentation of analysis (working with do- and log-files)
• data aggregation and data formats
• uni- and bivariate data analysis and correlation
• simple graphs (histograms, bar charts, scatter plots, box plots)
• OLS-regression and logistic regression

On both days, participants will have the opportunity for individual counselling after the workshop from 3:00pm to 4:00pm.

In cooperation with

Competence Center for Empirical Research Methods

• Introduction to the basic features of Stata
• Help functions and web resources
• Data management (import/export of data, recoding, missing
  values, labels)
• By-prefix, system variables _n and _N
• Documentation of analysis (working with do- and log-files)
• Data aggregation and data formats
• Uni- and bivariate data analysis and correlation
• Simple graphs (histograms, bar charts, scatter plots, box plots)
• OLS-regression and logistic regression