Dear list members I have a doubt on how p-values for t-statistics are calculated in the summary of Linear Models.
Here goes an example: x <- rnorm(100,50,10) y <- rnorm(100,0,5) fit1<-lm(y~x) summary(fit1) summary(fit1)$coef[2] # b summary(fit1)$coef[4] # Std. Error summary(fit1)$coef[6] # t-statistic summary(fit1)$coef[8] # Pr(>|t| summary(fit1)$df [2] # degrees of freedom # t-statistic can be calculated as: t<-(summary(fit1)$coef[2])/summary(fit1)$coef[4] t # t-statistic # the critical value for t0.05(2)df can be obtained in a t distribuition table # http://www.math.unb.ca/~knight/utility/t-table.htm or with qt(0.975,summary(fit1)$df[2]) # Two-sided p-value should be estimated with dt(t,summary(fit1)$df[2]) # isn't it? But this value is different from summary(fit1)$coef[8] My question is: how to reach to the same p-value indicated in Pr(>|t|) or summary(fit1)$coef[8]? Thanks in advance, Antonio Olinto [[alternative HTML version deleted]] ______________________________________________ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
