The talk will start by giving a summary of Econometrics and Machine Learning, explaining their association with prediction and causality, and diving into their differences through the linear regression model. Since linear regression models are widely used in academics as well as industry, the talk would provide a great platform to understand these broad topics given its adaptability for a wide range of applications. The talk would then review some of the statistics involved in linear regression models and explain how their intuition changes when interpreted under prediction or causality. The idea is to give undergraduate students a sense of these fields rather than expecting them to know everything in an hour-long session. 

Dr Parush Arora is an Assistant Professor of Economics at Ashoka University. He did his PhD in Economics from the University of California, Irvine. His primary research interests are Econometrics, Bayesian Inference, and Empirical Macroeconomics. He holds a Bachelor’s in Economics from the University of Delhi and a Master’s in Economics from the Madras School of Economics.

The talk is mandatory for the students of DATA202 and DATA203.

All are welcome!