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Telescopes are much more expensive than astronomers, so it is essential tominimize required sample sizes by using the most data-efficient statisticalmethods possible. However, the most commonly used model-independent techniquesfor finding the relationship between two variables in astronomy are flawed. Inthe worst case they can lead without warning to subtly yet catastrophicallywrong results, and even in the best case they require more data than necessary.Unfortunately, there is no single best technique for nonparametric regression.Instead, we provide a guide for how astronomers can choose the best method fortheir specific problem and provide a python library with both wrappers for themost useful existing algorithms and implementations of two new algorithmsdeveloped here.

Nonparametric Methods in Astronomy: Think, Regress, Observe -- Pick Any Three