Silverman's rule of thumb

Silverman's rule of thumb is a method used to choose the width of the "bins" or "bandwidth" when estimating the shape of a data distribution, such as with a histogram or a smooth density curve. It suggests a formula based on the data’s standard deviation and size, aiming to strike a balance between over-smoothing (losing detail) and under-smoothing (highlighting noise). Essentially, it provides a practical, quick way to select a bandwidth that helps accurately represent the underlying data pattern without manually fine-tuning it.