Being able to make conclusions about data trends is one of the most important steps in both business and science. Through the magic of least sums regression, and with a few simple equations, we can ...

The simplest form of regression in Python is, well, simple linear regression. With simple linear regression, you're trying to ...

This example uses the corn yield data from the previous example to illustrate how to construct a regression estimator for a stratified sample design.

Stepwise regression involves selection of independent variables to use in a model based on an iterative process of adding or removing variables.

If the dots tightly adhere to the zero baseline, the regression equation is reasonably accurate. If the dots are wildly scattered, the regression equation may have limited usefulness.

For example, with a cutpoint of 0.5, 4 events and 16 nonevents were classified correctly. On the other hand, 2 nonevents were incorrectly classified as events and 5 events were incorrectly classified ...

This paper is an exposition of the use of ridge regression methods. Two examples from the literature are used as a base. Attention is focused on the RIDGE TRACE which is a two-dimensional graphical ...

Both dispersion modeling (DM) and land-use regression modeling (LUR) are often used for assessment of long-term air pollution exposure in epidemiological studies, but seldom in combination.