01 Losing Female Talent


Miklós Koren

Miklós teaches reproducible coding practices to economists to help them maximize their scientific impact. He believes in the command line, plain text, and that every problem can be solved with the right combination of Stata, Python, Julia, git, and make. He is Professor of Economics at Central European University and the Data Editor of the Review of Economic Studies, a leading scientific journal.

01 Losing Female Talent

This course is an immersive simulation game designed for professionals and executives to provide an introduction to descriptive and predictive analytics, enabling them to leverage data in their organizations. The objectives of the course include finding patterns using basic statistical concepts, modelling processes with regression, and understanding potential biases during the analyses. The focus is on interpreting and communicating data analysis results rather than performing statistical calculations. Various assignments, including readings, essays, and presentations, reinforce the learned concepts. Based on the feedback of the participants, the simulation proved to be engaging, promoting active participation and fruitful discussions. Overall, this course contributes to the understanding of data-driven decision making, enhances data analytics skills and fosters critical thinking and communication abilities.

You will learn to
  • Evaluate whether a sample is appropriate for a particular purpose.
  • Use multivariate regression to compute the mean of an outcome conditional on other variables.
  • Use causal graphs to illustrate how three or more factors are related.
  • Critically evaluate statistical analysis based on subject matter expertise and general human judgement.

This course has been developed with support from a Teaching Development Grant of CEU.