$\backslash$table$[[,$Demand$],[$January$,12],[$February$,11],[$March$,15],[$April$,12],[$May$,16],[$June$,15]]$

a$.$ Using a weighted moving average with weights of $0\mathrm{.}60,0\mathrm{.}30,$ and $0\mathrm{.}10,$ find the July forecast.

b$.$ Using a simple $3-$month moving average, find the July forecast.

c$.$ Using single exponential smoothing with $a=0\mathrm{.}2$ and a June forecast ~~$13,$ find the July forecast. Make whatever assumptions you wish.

d$.$ Using simple linear regression analysis, calculate the regression equation for the demand data.

e$.$ Using the regression equation in $d,$ calculate the forecast for July.