Now that you've got a good sense of how to 'speak' R, let's use it with linear regression to make distinctive predictions.

The bottom line is this: You cannot meaningfully compare the size of the regression coefficients to assess the most important effect—it is an apples-and-oranges comparison.

Discover how linear regression works, from simple to multiple linear regression, with step-by-step examples, graphs and real-world applications.

Research on multiple comparison during the past 50 years or so has focused mainly on the comparison of several population means. Several years ago, Spurrier considered the multiple comparison of ...

A new multivariate concept of quantile, based on a directional version of Koenker and Bassett's traditional regression quantiles, is introduced for multivariate location and multiple-output regression ...

One common problem in the use of multiple linear or logistic regression when analysing clinical data is the occurrence of explanatory variables (covariates) which are not independent, ie ...