a$)$ After plotting the data, we can observe that the most appropriate forecasting technique is

Exponential Smoothing

$.$

b$)$ The overall average of demand across all provided periods is

$133\mathrm{.}33$

units.

c$)$ For each period, select the multiplicative seasonal index factor from the dropdown list.

Period Seasonal Factor

Jan$-$Feb

$0\mathrm{.}83$

Mar$-$Apr

$1\mathrm{.}19$

May$-$Jun

$1\mathrm{.}36$

Jul$-$Aug

$0\mathrm{.}80$

Sep$-$Oct

$0\mathrm{.}95$

Nov$-$Dec

$0\mathrm{.}83$

d$)$ The regression line fitting the deseasonalized demand has an intercept of

$123$

and a slope of

$123$

$.$

e$)$ Using the results from the previous parts, what is the forecast including trend and seasonality $($FITS$)$ for each period of the next year?

Period FITS

Jan$-$Feb

$112$

Mar$-$Apr

$[$ Select $]$

May$-$Jun

$[$ Select $]$

Jul$-$Aug

$[$ Select $]$

Sep$-$Oct

$[$ Select $]$

Nov$-$Dec

$[$ Select $]$