Re: [R] Understanding the intercept value in a multiple linear regression with categorical values

Hi! You're right. I was misinterpreting the way the coefficients were calculated. Reading about the method of least squares helped me in clarifying some of my doubts. Thanks for your tips! -- Joao. On Fri, Jul 27, 2012 at 2:36 PM, Jean V Adams jvad...@usgs.gov wrote: Joao, Your intuition

[R] Understanding the intercept value in a multiple linear regression with categorical values

Hi! I'm failing to understand the value of the intercept value in a multiple linear regression with categorical values. Taking the warpbreaks data set as an example, when I do: lm(breaks ~ wool, data=warpbreaks) Call: lm(formula = breaks ~ wool, data = warpbreaks) Coefficients: (Intercept)

Re: [R] Understanding the intercept value in a multiple linear regression with categorical values

Joao, There's a very thorough explanation at http://www.ats.ucla.edu/stat/r/library/contrast_coding.htm Jean Joao Azevedo joao.c.azev...@gmail.com wrote on 07/27/2012 06:32:31 AM: Hi! I'm failing to understand the value of the intercept value in a multiple linear regression with

Re: [R] Understanding the intercept value in a multiple linear regression with categorical values

Hi! Thanks for the link. I've already stumbled upon that explanation. I'm able to understand how the coding schemes are applied in the supplied examples, but they only use a single explanatory variable. My problem is with understanding the model when there are multiple categorical explanatory

Re: [R] Understanding the intercept value in a multiple linear regression with categorical values

Joao, Your intuition is correct, the intercept represents the predicted value for wool A and tension L. But, you're tripping up on how to figure out that predicted value. In the model that you fit, the predicted value for wool A and tension L is not simply the mean of the observations for