In most applications, regression models are merely useful approximations. Reality is often so complicated that you cannot know what the true model is. You may have to choose a model more on the basis ...

Mitchell Grant is a self-taught investor with over 5 years of experience as a financial trader. He is a financial content strategist and creative content editor. Timothy Li is a consultant, accountant ...

This example shows a regression module that calculates statistics not calculated by the two previous examples: /* Regression Routine */ /* Given X, and Y, this fits Y ...

Examination of the (sample) residuals resulting from the regression analysis can indicate failures of assumptions 1, 3, and 4. Such failures are not necessarily a bad thing: They can point the way to ...

Some of you may have come across a growing number of publications in your field using an alternative paradigm called Bayesian statistics in which to perform their statistical analyses. The goal of ...

BACKGROUND The application of geographically weighted regression (GWR) – a local spatial statistical technique used to test for spatial nonstationarity – has grown rapidly in the social, health, and ...

Journal of the Royal Statistical Society. Series C (Applied Statistics), Vol. 48, No. 3 (1999), pp. 313-329 (17 pages) The number of variables in a regression model is often too large and a more ...

A two-valued qualitative variable can be represented by a single 0-or-1-valued "dummy" variable. If a qualitative variable has three or more possible values (e.g., make-of-car, or marital-status), ...