> fit <- lm(w ~ c + h + o + g, data=mydata)
> summary(fit)

Call:
lm(formula = w ~ c + h + o + g, data = mydata)

Residuals:
    Min      1Q  Median      3Q     Max
-0.4926 -0.2208 -0.2208  0.5074  0.7792

Coefficients: (1 not defined because of singularities)
            Estimate Std. Error t value Pr(>|t|)
(Intercept) 0.220759   0.006037  36.566  < 2e-16 ***
c           0.271846   0.015930  17.065  < 2e-16 ***
h           0.083388   0.014578   5.720 1.10e-08 ***
o           0.114292   0.016811   6.799 1.13e-11 ***
g                 NA         NA      NA       NA
---
Signif. codes:  0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1

Residual standard error: 0.4371 on 7977 degrees of freedom
Multiple R-squared:  0.03833,   Adjusted R-squared:  0.03797
F-statistic:   106 on 3 and 7977 DF,  p-value: < 2.2e-16