Confusion regarding model order and lags
Hi: As far as what you wrote in confusion 2): 

The AR expression should not have an $x[t]$ on both sides. For example, below is an AR(2):

$x[t] = a1*x[t-1] + a2*x[t-2]+ e[t]$

Similarly, the MA expression should always have a coefficient of 1 on the  $e[t]$ term. So, for example, an MA(2) would be:

$x[t] = e[t] + a1*e[t-1] + a2*e[t-2]$

As Stanley said, it is only a matter of convention but the order of an AR(p) is generally thought of as $p$ so there are $p$ AR coefficients if the order is p. Similarly, for an MA(q) there are q MA coefficients so the order is considered to be q ( the $e[t]$ is not included in the order for an MA because there is no coefficient associated with $e[t]$). 

Note that, for both MA and AR models,  the number of parameters to be estimated is not always equal to the order of the model because there may be non zero mean terms or trend terms. For example, below is AR(2) with unknown mean $\mu$:

$x[t] = \mu + a1*x[t-1] + a2*x[t-2]+ e[t]$.

Note that there are also ARMA models where the number of coefficients is then p+q. For example, an ARMA(2,1) is:

$x[t] = a1*x[t-1] + a2*x[t-2]+ b1*e_[t-1] + e[t]$.

But usually the term "order" is not used for ARMA models.

I hope this makes it clear.