[Statistics] The Origin of the Term 'Regression'

This post covers understanding the etymology of the term 'regression' in statistics.

1. Introduction

In the realm of statistics, regression analysis is a fundamental technique used to model relationships between variables. From predicting stock prices to analyzing disease risk factors, regression has found its applications in numerous domains. But have you ever wondered why this statistical approach is called "regression"? In this blog post, we'll delve into the fascinating history of regression, tracing its origins and unveiling the intriguing story behind its name.

2. Historical Origins

The term "regression" in statistics can be attributed to Sir Francis Galton, a polymathic scientist and cousin of Charles Darwin. Galton is renowned for his groundbreaking contributions to various fields, including genetics, psychology, and statistics.

In the late 19th century, Galton was investigating the relationship between the heights of parents and their offspring. He noticed an interesting phenomenon: extreme heights tended to "regress" or move closer to the population average in subsequent generations. This observation led him to coin the term "regression" to describe this statistical concept.

3. Historical Usage

Interestingly, the term "regression" was not initially used exclusively in the context of linear regression. It had a broader meaning and was employed to describe any trend that deviated from a previous state and moved towards an average or mean. This usage of the term was prevalent until Karl Pearson, another prominent statistician, introduced the concept of linear regression as we know it today.

4. The Conceptual Significance

The term "regression" in the context of linear regression carries a profound conceptual significance. It highlights the idea that extreme values of the dependent variable tend to "regress" towards the mean when related to the independent variables. In other words, it suggests a tendency for the observed values to move back or "regress" to the overall trend represented by the line of best fit.

5. Conclusion

The origin of the term "regression" in statistics can be traced back to the observations and work of Sir Francis Galton. Their investigations into phenomena involving the movement of extreme values towards the mean laid the foundation for the concept we now know as regression analysis. Today, regression remains a powerful statistical tool for modeling relationships between variables and making predictions. Understanding the historical context behind its name adds a layer of intrigue to this essential statistical technique and reminds us of the rich and evolving nature of statistical research and discovery.