This course is focused on dealing with omitted variables problems that can result in inaccurate forecasts when using financial data. The focus of this module is on dealing with the problem of missing data; an issue that impacts almost all large scale Big Data projects.
Prerequisites
Viewers should be familiar with basic financial and accounting concepts.
In addition, viewers should be familiar with Big Data and Business Intelligence, or review my existing courses on the topic.
Learning Objective
- Recognize what omitted variables are
- Identify omitted variables in a dataset
- Explore how to deal with omitted variables
- Discover how to correct for omitted variables and make a forecast
Last updated/reviewed: July 6, 2025
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Michael McDonald
President
INTRODUCTION AND OVERVIEW
- Introduction and Module 1: Omitted Variables Overview 12:32
- Module 2: Correcting for Omitted Variables 6:04
- Module 3: Choosing Variables in Regressions 8:48
- Module 4: Data Mining 10:16
- Module 5: Choosing Variables in Practice & Conclusion 12:36
CONTINUOUS PLAY
SUPPORTING MATERIALS
- Slides: Advanced Analytics – Dealing with Omitted Variables Problems PDF
- Advanced Analytics – Dealing with Omitted Variables Problems Glossary/Index PDF
REVIEW AND TEST
- REVIEW QUESTIONS quiz
- FINAL EXAM exam
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