DATA TO DECISIONS

Prerequisites & course information

Requisites: Declared in an MBA program Course Designation: Grad 50% - Counts toward 50% graduate coursework requirement Repeatable for Credit: No Last Taught: Fall 2026 Learning Outcomes: 1. Read, clean, create new datasets Audience: Graduate 2. Describe the resulting data by computing and interpreting summary statistics, and via visualization tools Audience: Graduate 3. Describe uncertainty and risk using the language of probability theory Audience: Graduate 4. Perform hypothesis tests common in business applications Audience: Graduate 5. Perform Monte Carlo simulations Audience: Graduate 6. Estimate cross-sectional and time-series models for forecasting purposes and select among competing models via cross-validation Audience: Graduate 7. Apply machine learning methods in the context of simple examples Audience: Graduate Learning Outcomes: 1. Read, clean, create new datasets Audience: Graduate 2. Describe the resulting data by computing and interpreting summary statistics, and via visualization tools Audience: Graduate 3. Describe uncertainty and risk using the language of probability theory Audience: Graduate 4. Perform hypothesis tests common in business applications Audience: Graduate 5. Perform Monte Carlo simulations Audience: Graduate 6. Estimate cross-sectional and time-series models for forecasting purposes and select among competing models via cross-validation Audience: Graduate 7. Apply machine learning methods in the context of simple examples Audience: Graduate