ADF test --time series

a) This looks like homework. The Posting Guide clearly indicates that this list is not for homework help.

b) This is a statistics theory question that happens to use R, not an R question that happens to be about statistics. Also off-topic per the Posting Guide... there are other forums for stats questions.
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Sent from my phone. Please excuse my brevity.

Hi all,

I was running the adf test in R.


CODE 1:

adf.test(data$LOSS)

       Augmented Dickey-Fuller Test

data:  data$LOSS
Dickey-Fuller = -1.9864, Lag order = 2, p-value = 0.5775
alternative hypothesis: stationary


CODE 2:
adf.test(diff(diff(data$LOSS)))

       Augmented Dickey-Fuller Test

data:  diff(diff(data$LOSS))
Dickey-Fuller = -6.9287, Lag order = 2, p-value = 0.01
alternative hypothesis: stationary



Is my interpretation correct:

The original data( in code 1) is not stationary

the twice differenced data (in code 2) is *stationary* and the order of
the
corresponding ARMA(p,q) model are *p=2* (as lag order in the output is
2)
and *q=0*;.i.e. the *AR coefficients for X(t-1) and X(t-2) are
significant*,
while those of X(t-3) onwards are insignificant.


Appreciate your help.
Thanks,
Preetam