Eg:

> library(ISwR)

> fit <- lm(metabolic.rate ~ body.weight, rmr)

> summary(fit)

Call:

lm(formula = metabolic.rate ~ body.weight, data = rmr)

Residuals:

    Min      1Q  Median      3Q     Max

-245.74 -113.99  -32.05  104.96  484.81

Coefficients:

            Estimate Std. Error t value Pr(>|t|)   

(Intercept) 811.2267    76.9755  10.539 2.29e-13 ***

body.weight   7.0595     0.9776   7.221 7.03e-09 ***

---

Signif. codes:  0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1

Residual standard error: 157.9 on 42 degrees of freedom

Multiple R-squared: 0.5539, Adjusted R-squared: 0.5433

F-statistic: 52.15 on 1 and 42 DF,  p-value: 7.025e-09

The 95% confidence interval for the slope is the estimated coefficient (7.0595) ± two standard errors (0.9776).

his can be computed using confint:

> confint(fit, 'body.weight', level=0.95)

               2.5 % 97.5 %

body.weight 5.086656 9.0324