Maastricht, Netherlands

Data Analysis using STATA

when 24 June 2019 - 29 June 2019
language English
duration 1 week
fee EUR 850

The 6-day course is a practical introduction to statistic and econometric methods using STATA. You will improve your data handling, analysis and interpretation skills needed to carry-out your own empirical project. You will also gain familiarity with gathering and using large secondary data sets and learn how big data can be utilized.

During the course the fundamentals of regression analysis as well as applied topics related to estimation and inference for probability models, panel data, difference-in-differences and instrumental variables will be covered. Throughout the course, each topic is explained using examples based on real data. The course is hands-on, all computer sessions will be used to replicate results from research articles in finance and economics.

The course will rigorously introduce you to the methods but without the mathematical details behind the models. You will gain a clear understanding of when and how to apply the different models and of their limitations. The course puts an extra emphasis on visualizing regression models and will use graphical intuition to improve the understanding of more advanced topics.

Target group

The program targets
PhD students/DBA students
Post-Doctoral students
Post-graduates students

Who is the program designed for:
Participants should be familiar with basic statistics. No prior knowledge of regression models or of STATA is necessary. The course is appropriate for doctoral students and academic researchers who plan to improve their knowledge of quantitative research methods.

Course aim

Learning outcomes
Gain an in-depth understating of analyzing data using STATA
Develop ability to estimate and interpret econometric models in STATA
Be able to cross-tabulate data and construct complex graphs
Understand how to run multiple regression and panel data models
Be able to write short programs in STATA to input, manage and analyze large data sets

Fee info

EUR 850: Early Bird Fee (registration until 20 April 2019): € 780
Regular Fee (registration after 20 April 2019): € 850