Statistical techniques are tools that enable us to answer questions about possible patterns in empirical data. It is not surprising, then, to learn that many important techniques of statistical analysis were developed by scientists who were interested in answering very specific empirical questions. So it was with regression analysis. The history of this particular statistical technique can be traced back to late nineteenth-century England and the pursuits of a gentleman scientist, Francis Galton. Galton was born into a wealthy family that produced more than its share of geniuses; he and Charles Darwin, the famous biologist, were first cousins. During his lifetime, Galton studied everything from fingerprint classification to meteorology, but he gained widespread recognition primarily for his work on inheritance. His most important insight came to him while he was studying the inheritance of one of the most obvious of all human characteristics: height. In order to understand how the characteristic of height was passed from one generation to the next, Galton collected data on the heights of individuals and the heights of their parents. After constructing frequency tables that classified these individuals both by their height and by the average height of their parents, Galton came to the unremarkable conclusion that tall people usually had tall parents and short people usually had short parents.
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© 1997 Plenum Press, New York
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(1997). The origins and uses of regression analysis. In: Understanding Regression Analysis. Springer, Boston, MA. https://doi.org/10.1007/978-0-585-25657-3_1
Publisher Name: Springer, Boston, MA
Print ISBN: 978-0-306-45648-0
Online ISBN: 978-0-585-25657-3
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