Regression

 the concept of regression models and their significance in statistical analysis, using the example of the height of children born to tall parents. The author highlights the potential consequences if successive generations consistently became taller, emphasizing the practical limitations in terms of furniture, cars, and planes. Sir Frances Galton's 1886 study on this issue led to the development of regression models, which have since become integral in various fields, including medicine, business, and academia.

The narrative introduces regression models through a personal story about the author's Master's thesis on hedonic price models for residential real estate properties. The example involves studying the determinants of housing prices, with the author's wife expressing amusement at the seemingly obvious conclusion that larger homes sell for more than smaller ones. The author then explains the intricate aspects of the research, focusing on the magnitude of relationships and uncovering nuanced insights, such as the impact of additional washrooms on housing prices.

The Department of Obvious Conclusions is humorously depicted, highlighting the challenge of conveying the depth of research findings to those familiar with common knowledge. The author emphasizes the value of quantifying relationships and the role regression models play in addressing various questions related to housing markets. Examples of such questions include the influence of additional bedrooms, lot size, exterior materials, finished basements, and proximity to certain features on housing prices.

The chapter concludes by posing questions that regression analysis can address, underlining the versatility and applicability of regression models in exploring complex relationships and contributing valuable insights in different domains.