Introductory Econometrics: Regression Basics

[This course contains the use of artificial intelligence.] - Voiceover

Understanding relationships between variables is at the heart of econometrics, and regression analysis is the key tool for this task. This course, Introductory Econometrics: Regression Basics, is designed for beginners, students, and professionals who want a clear, practical introduction to regression techniques and interpretation. You’ll learn how to build, estimate, and interpret regression models using real-world examples, giving you a strong foundation for advanced econometrics and data-driven decision-making.

The course begins with an introduction to regression models. You will first explore simple regression, analyzing the relationship between a single independent variable and a dependent variable, and then move to multiple regression, which allows you to examine the effect of several predictors simultaneously.

Next, you’ll focus on interpretation. You will learn how to understand the slope and intercept of a regression line, and how to distinguish the intercept from the error term. These concepts are crucial for interpreting the results of your models accurately.

The course also covers estimation techniques. You will gain a solid understanding of the Ordinary Least Squares (OLS) method, including the underlying formulas, key properties, and the concept of partialling out, which allows you to isolate the effect of individual variables in a multiple regression context.

By the end of this course, you will be able to estimate regression models confidently, interpret coefficients meaningfully, and understand the assumptions and properties behind OLS estimation. These skills will provide a practical foundation for analyzing real-world economic and business data and for progressing to more advanced econometric methods.