Consider a time series $\{y_t\}$ where:

$\{y_t\}$ follows a random walk model and $\{c_t\}$ is from a white noise process.

$c_6=1,c_7=2,c_8=4,c_9=3$

The average of $c_1$ through $c_5$ is $1\mathrm{.}5.$

$y_0=20$

The $4-$step ahead forecast of $y_9,$hat$(y{)}_9,$ is based on $y_5.$

Determine which of the following statements is true.

$y_5=26\mathrm{.}5$

$y_9=36\mathrm{.}5$

hat$(y{)}_9=32\mathrm{.}5$

The forecast error for the time series at time $9$ is $3.$