Thanks to Tiffany for bringing my attention to the fact that the solution to the second example in the review lesson for E.2 was not consistent with the solutions to somewhat similar problems from old exams and sample exams.

I think that this lesson problem was not being solved the way that you would be expected to solve it on an exam, so I’ve removed that problem.

The source text we are using utilizes these two routines in R:
The ar routine in R subtracts the mean before estimating and does not report a mean or an estimate. It is up to us to compute the mean separately and mean adjust as necessary.
The arima routine spits out an intercept whenever d = 0, and that “intercept” is to be understood as an estimate for the mean, and not as a traditional GLM style intercept that we just add into the right-hand side of the model.

This issue has come up one time on previous exams, on Exam S Fall 2016 #43.
On this exam problem, they provided an intercept in the output, but they didn’t say what routine was used to produce it. If you assumed that it was the arima, so that you mean-adjusted, then you got the preliminary answer key result. However, they eventually also accepted the answer that you get by using the intercept as an intercept instead of mean adjusting, probably because they didn’t say where the intercept was coming from or what it should have represented. I think there is a high likelihood that when they get back around to testing this, they will try to make it more clear what is expected.

Additionally, this week problems were added to D.6.3, D.4.4, D.4.2, and D.4.1.