[R] Regression Testing

[Mojo]

I'm new to R and some what new to the world of stats.  I got frustrated 
with excel and found R.  Enough of that already.

I'm trying to test and correct for Heteroskedasticity

I have data in a csv file that I load and store in a dataframe.

 > ds <- read.csv("book2.csv")
 > df <- data.frame(ds)

I then preform a OLS regression:

 > lmfit <- lm(df$y~df$x)

To test for Heteroskedasticity, I run the BPtest:

 > bptest(lmfit)

         studentized Breusch-Pagan test

data:  lmfit
BP = 11.6768, df = 1, p-value = 0.0006329

 From the above, if I'm interpreting this correctly, there is 
Heteroskedasticity present.  To correct for this, I need to calculate 
robust error terms.  From my reading on this list, it seems like I need 
to vcovHC.

 > vcovHC(lmfit)
               (Intercept)         df$x
(Intercept)  1.057460e-03 -4.961118e-05
df$x       -4.961118e-05  2.378465e-06

I'm having a little bit of a hard time following the help pages.  So is 
the first column the intercepts and the second column new standard errors?

Thanks,
mojo