We observe a series of observations:
\(x_1, x_2,...,x_t)\)
What can we say about \(x_{t+1}\)?
If the data was drawn iid then the past data then we would just want to identify moments.
However if the data is not iid, for example because it is increasing in time, then this is not the best way.
We can model
\(x_t=\alpha + \epsilon_t\)