[R] linear model - lm (Adjusted R-squared)?

From: Brian Smith <bsmith030465_at_gmail.com>
Date: Fri, 04 Mar 2011 08:54:42 -0500


Hi,

Sorry for the naive question, but what exactly does the 'Adjusted R-squared' coefficient in the summary of linear model adjust for?

Sample code:

> x <- rnorm(15)
> y <- rnorm(15)
> lmr <- lm(y~x)
> summary(lmr)

Call:
lm(formula = y ~ x)

Residuals:

    Min 1Q Median 3Q Max
-1.7828 -0.7379 -0.4485 0.7563 2.1570

Coefficients:

            Estimate Std. Error t value Pr(>|t|) (Intercept) -0.13084 0.28845 -0.454 0.658 x 0.01923 0.25961 0.074 0.942

Residual standard error: 1.106 on 13 degrees of freedom Multiple R-squared: 0.0004217, Adjusted R-squared: -0.07647 F-statistic: 0.005485 on 1 and 13 DF, p-value: 0.942

> cor(x,y)
[1] 0.02053617

many thanks!

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