This course is aimed at all MBAs who expect at some point in their careers to use, understand and apply statistical methods that can enhance their data understanding and support their decisions.
The objective of the course is to provide a theoretical background and empirical abilities in working with data. Students will work with various statistical tools, ranging from simple descriptive statistics, to regression, time series, and modern machine learning methods. The course builds on the previous statistics and econometrics courses which the students have studied.
Course Content and Organization
Students will be exposed to a number of techniques that cover the most general situations. The course will cover essentially three big topics:
- Working with Python, with a focus on data analysis and simple regressions methods. The students will learn how to work with data, do simple descriptive statistics, and use Python for regression analysis
- Understanding and gaining knowledge on use time series tools. This will cover the basics of time series, and also models used in finance (ARCH, GARCH).
- Machine learning techniques, were the focus will be on modern approaches to work with data, ranging from Lasso techniques, to text analysis and classification. Students will learn how to use these models in the specific context of economic and business data.
- Finally, the last component is dedicated to a project. Students will use what they learned in the context of doing a specific research project where the data will be analyzed and the results discussed. The format of the project will take the form of a research paper.