ChatGPT $3\mathrm{.}5$

User

Period.

$1$

$2$

$3$

$4$

$5$

$6$

$7$

Demand

$73$

$80$

$73$

$75$

$74$

$75$

$78$

F$1$

$75$

$75$

$75$

$75$

$76$

$76$

$76$

F$2$

$75$

$76$

$72$

$73$

$73$

$77$

$74$

a$-1.$ Calculate the MAD for each set of forecasts. $($Round the final answers to $2$ decimal places.$)$

E

F$1$

F$2$

$01$:$07\mathrm{.}4$B

a$-2.$ Which technique appears to be more accurate?

$($Click to select$)$ v

$=$Book

b$-1.$ Calculate the MSE for each set of forecasts. $($Round the final answers to $2$ decimal places.$)$

Fl

F$2$

b$-2.$ Which technique appears to be more accurate?

Click to select$)$Y

c$-1.$ Calculate the MAPE for each set of forecasts. $($Round the final answers to $2$ decimal places.$)$

F$1$

F$2$

c$-2.$ Which technique appears to be more accurate?

$($Click to select$)$v

Book

d$-1.$ Do all three of forecast errors provide the same conclusion $($i$.$e$.,$ are they consistent$)$ in this case?

$($Click to select$)$ v

d$-2.$ Do you expect consistent results in every case?

$($Click to select$))$

$($Click to select$)$v will have lower MSE than $($Click to select$)$ v$]$ if obs $7$ for F$1$ was $81.$

e$.$ In practice, either MAD, MSE, or MAPE would be employed to compute a measure of forecast errors. What factors might lead a

manager to favour one?

MAD

MSE

MAPE

$($Click to select$)$

$($Click to select$)$

$($Click to select$)$