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|Table of Contents Bivariate Data Regression Leverage Effect|
|See also: regression, outliers|
The term "leverage" is commonly used for an undesirable effect which
is experienced with regression analysis (as well as with other methods).
It basically means that a single data point which is located well outside
the bulk of the data (an "outlier") has an overproportional effect on the
resulting regression curve. A simple interactive example will demonstrate
this effect. Depending on the number of the samples and the distance of
the outlier from the rest of the data, this effect may completely corrupt
a regression model which would be quite good in the absence of an outlier.
In order to start the interactive example click on the figure below.
Last Update: 2005-Jul-16