Tepper · MS in Business Analytics
46-880 Introduction to Probability and Statistics
Probability and inference taught twice over, in Excel and in Python, through business decisions.
The first quantitative course in the full-time MS in Business Analytics: probability, distributions, sampling, estimation, hypothesis tests, and regression.
Topics
- Probability and Bayes' theorem
- Discrete and continuous random variables and their distributions
- The normal distribution and joint distributions
- Sampling and the central limit theorem
- Interval estimation
- Hypothesis testing
- Regression, and inference with regression
How the course works
Every distribution is taught twice, once with its Excel formula and once with its Python call, and nearly every example is a business decision: overbooking a flight, a cosmetics launch whose chance of success moves from 30% to 60% after a market test, tea bottles that must hold 750 ml. Sessions open with a puzzle or a question from quant interviews.
Halfway through the seven-week term I changed the pace: more worked examples in class, practice sets with solutions, a short written summary of each module, and walkthrough videos for the hardest problems.
How the course developed
I taught the MS in Business Analytics program's first-term statistics course in Fall 2024, in two morning sections. I reworked the slide decks I inherited and used Excel and Python alongside the textbook, so that every idea had both a formula and a working example.
Offerings
- Fall 2024 full-time
Students received the problem sets and walkthrough videos on Canvas.