Comparing two regression line slopes

Hello R users,
I've used the following help:

  

"Comparing two regression line slopes"
I knew the method based on the following statement :
t = (b1 - b2) / sb1,b2
where b1 and b2 are the two slope coefficients and sb1,b2 the pooled  
standard error of the slope (b)

which can be calculated in R this way:

 > df1 <- data.frame(x=1:3, y=1:3+rnorm(3))
 > df2 <- data.frame(x=1:3, y=1:3+rnorm(3))
 > fit1 <- lm(y~x, df1)
 > s1 <- summary(fit1)$coefficients
 > fit2 <- lm(y~x, df2)
 > s2 <- summary(fit2)$coefficients
 > db <- (s2[2,1]-s1[2,1])
 > sd <- sqrt(s2[2,2]^2+s1[2,2]^2)
 > df <- (fit1$df.residual+fit2$df.residual)
 > td <- db/sd
 > 2*pt(-abs(td), df)

Using my data I finally get the value of the test, which is: 2.245e-7.
Do my slopes differ significantly now?
Thanks for help,  Benedikt
 

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