Advanced Data Analysis

This is a program providing students with practical and hands-on knowledge in doing advanced analyses such as impact evaluations and health inequality analyses. 


 ADA100: Sampling and power analysis


This course provides students with skills in determining and analyzing the required sample. Statistical power analysis is an important technique in the design of experiments that helps a researcher to determine how big a sample size should be selected for an experiment.


ADA200: Advanced data analytics


Students will learn advanced methods in econometrics and biostatistics such as:

  • Data mining techniques: principal component analysis, factor analysis, etc.

  • Regression models for categorical variables

  • Survival analysis

  • Generalized linear modelling


ADA300: Measuring health inequalities


Upon successfully completing this course, students will be able to understand what is meant by the term ‘social determinants of health; how these determinants are linked to inequality in health outcomes between different social groups; and what potential exists to do something positive about these inequalities.  The students will also able to make a clear distinction between inequality and equity and to carry out basic inequality analyses in providing health care and financing.  


ADA400: Impact Evaluation Experiment methodologies


This course will cover the ABC for the following methods:

  • Experimental method, i.e. randomized control trial

  • Non experimental methods such as matching techniques, difference-in-difference, instrumental variables, regression discontinuity analysis.


ADA900: Advanced data analysis project


Under the technical assistance of lecturer or another professional researcher, the student will develop a practical research project and present results to the panel of researchers.

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