Business Analytics 830 - Business Experimentation and Causal Methods

Instructor: Professor Andrey Fradkin

Office: Questrom 617, Zoom

Office hours:

YOU MUST BOOK BEFOREHAND AT THIS LINK: https://calendly.com/afradkin/15min

Instructor Email: [email protected], but please try Slack first.

Zoom link for Prof. Fradkin’s office hours: https://bostonu.zoom.us/my/afradkin

TA Office Hours:

Oriol Ripalta I Maso ([email protected])

OH: Fri 3pm - 4:30pm


Chandrahas Aroori ([email protected])

OH: Wed 2pm - 3:3-pm

Meeting Times:

Tue, Thursday

8:00am - 10:45am (Morning Section)

12:30pm to 3:15pm (Afternoon Section)

In-Person Room:

HAR 312 (Afternoon)

HAR 224 (Morning)

See schedule schedule for guest speaker locations and exam location.


Key Links:


📜 Course Description

When is making a change to a price, algorithm, or product worthwhile? Rather than relying on the gut intuition of a manager, businesses are increasingly using experiments and other forms of causal data analysis to answer these questions. In this class, we will learn about causal methods, when they work, how to implement them in Python, and how to apply them to topics including pricing, reputation system design, social networks, advertising, and algorithms.

🗝 Prerequisites

An enthusiasm for learning and using code to analyze data and a willingness to do some math.

A note on technical difficulty: The purpose of this class is to expose you to causal methods and how they can be applied to practical problems. Mathematical notation is very useful in precisely stating what assumptions these analyses make. That said, this class will not focus on the technical details of these statistical procedures. This means that if you’re interested in becoming a data scientist, I would encourage you to supplement the material in this class with appropriate classes in statistics, econometrics, and computer science.

Objectives and Learning Outcomes

At the end of the course, students should be able to: