Training Workshops on Data Analysis and Statistical Learning

This course provides an introductory training in R, a leading programming language and analytical package for data science. It is intended for those with limited or no previous experience in the said software. 

At the end of the course, participants should be able to:

• Familiarize themselves with the basic features and powerful statistical tools of R; and
• Gain working knowledge and experience on how to undertake basic research in the social sciences using R.

Requirements

Laptop, with installed R software

Registration Fee

PhP5,000/participant (inclusive of lunch, snack, kit, and certificate)

Trainers

Rocky Marcelino is an assistant professor at the Institute of Statistics as the University of the Philippines-Los Baños. With expertise in various statistical data mining and computational modelling techniques, he has delivered trainings in numerous academic, private and public sector organizations. He has also served as a research consultant for projects of the Department of Social Welfare and Development, the Department of Agriculture-Agricultural Credit Policy Council, UNICEF, the Australian Department of Foreign Affairs, and the Fundacion CODESPA (Embassy of Spain).

Jerik Cruz is a lecturer and economist based at the Ateneo de Manila University's Department of Economics. Having completed his Masters from the Graduate Institute of International and Development Studies in Geneva, he has done research, among others, for the Asian Development Bank, the International Labor Organization, the United Nations Research Institute for Social Development, the Friedrich Ebert Stiftung, the ISEAS Yusof-Ishak Institute of Singapore, the Department of Trade and Industry, on issues concerning urban development, trade, innovation, and inequality. He has previously delivered trainings on using R, STATA, and Python for data analysis.

This course provides an introductory training on statistical learning methods and focuses on key concepts, structures and processes, and practical issues in model assessment and validation. 

At the end of the course, participants should be able to:

• Understand the basic notion of statistical learning using parametric and nonparametric modeling frameworks;
• Implement basic commands and quantitative techniques in R to estimate linear and nonlinear regression models; and
• Implement techniques needed to ascertain model accuracy and adequacy.

Requirements

Laptop, with installed R software

Registration Fee

PhP5,000/participant (inclusive of lunch, snack, kit, and certificate)

Trainer

Lawrence Dacuycuy, Ph.D. is the current President of the Philippine Economic Society (PES). He is also a Regular Member of the National Research Council of the Philippines (NRCP) and Full Professor and Research Fellow at the School of Economics, De La Salle University. He currently sits as a member of the Commission on Higher Education’s (CHED) Technical Committee for Economics. He was the Dean of the School from 2013 to 2015.

He finished his BS Economics in 1998 at the School of Economics, University of the Philippines and two years thereafter, he received his Master of Science in Economics degree from the same university. He obtained his doctorate in economics from Kyoto University in 2006. 

His research focuses on applied nonparametric and semiparametric econometrics, labor economics, intergenerational social mobility, and macroeconomic modelling using Dynamic Stochastic General Equilibrium (DSGE) models. In 2009, he was one of the recipients of the National Academy of Science and Technology’s (NAST) Outstanding Young Scientist (OYS) award. In 2012, he was a recipient of the NAST Outstanding Scientific Paper Award for his research on wage functional analysis.