Gades Training presents Econometrics and Statistics Using R. The 5 training days provide the full set of tools and techniques that any modern applied researcher needs to know. Participants will learn the fundamental principles of modern statistics, econometrics, time series and forecasting, and will also learn how to apply the techniques properly using R software.
toc Expectations and Objectives
This course covers main practical aspects in statistical and Econometrics computing.
The objective of this course is to teach how to use R for successful data analysis. Particular focus is placed on the use of data to answer cause-and-effect questions and on the analysis of time-series data
This program is ideal for academic Staff, Masters / PhD students and professionals that need to analyse data regularly. This course will help you to expand your statistical and programming skills using R software.
Day 1 - Introduction to R
Day 2 - Introductory Statistics with R - Estimation and Hypothesis Testing
Day 3 - Causality in Econometrics 1 - OLS and Difff-in-Diff
Day 4 - Causality in Econometrics 2 - IV and Regression-Discontinuity-Designs
Day 5 - Time-series 1 - ARMA models and Forecasting
In-person instruction with hands-on R practice. The course will be taught in English.
Ratio: 50% Theory and 50% Practice
Materials used: R software (free).
- Only basic quantitative insight is required.
picture_in_picture Technological Resources
For this course will be used a free version of R software.
Our programs will put you in the lead of scientific knowledge and the latest tools used in statistics and econometrics.
Complete a R week to be an R certified professional. To get this certification, you’ll have to pass on our final exam. If you don’t submit to exam, you will receive a certificate of participation.
If you belong to an organization of the European Union (outside Portugal), you are exempt from VAT.
Currently Associate Professor at the Lisbon School of Economics and Management (ISEG). He obtained his master’s degree in statistics at the University of Amsterdam and his PhD in econometrics at University College London. He has taught undergraduate, masters and PhD courses in statistics and econometrics at the Vrije Universiteit Amsterdam, University College London and the London School of Economics.
His publications include articles in Health Economics and Journal of Business & Economic Statistics. He is an experienced consultant, with clients including the Ministry of Finance, Toronto, CA and the Institute for Fiscal Studies in London, UK.
Master in Econometrics and currently a PhD candidate in Applied Mathematics at the University of Lisbon.
His work has been published in the Statistics and Probability Letters. Additionally, he is a lecturer of statistics and econometrics courses at Lisbon School of Economics and Management (University of Lisbon) and the Information Management School (Nova University of Lisbon).