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Applied Statistics
Graduate Program (& Advanced Certificate) Status
Course Description

The aim of this course is to introduce advanced statistical methods – including variance analysis, nonparametric statistics, model selection, longitudinal data analysis, and statistical tricks and traps – and how to apply them in practice using python.

Learning Outcomes

By the end of the course students will be able to identify the most appropriate advanced statistical methods to be used to address a specific question, apply them to the available data, and interpret the results. Students will also be able to apply these methods to datasets curated by them and to address their own research questions.


Course assessment will be performed by means of a final project that will consist of the exploration, in python, of an open data set through an appropriate selection of the statistical methods introduced in class. The project can be fulfilled individually or in small groups of up to 3 students.


Knowledge of introductory statistics and basic data analysis skills in Python.

Course Level
Course Open to
Students on-site
Academic Year
US Credits
ECTS Credits
Course Code
UGST 4086