$\backslash$table$[[$Week$,\backslash$table$[[$Forecast$],[$Method $1]],\backslash$table$[[$Actual$],[$Demand$]]],[1,0\mathrm{.}90,0\mathrm{.}72],[2,1\mathrm{.}05,1\mathrm{.}05],[3,0\mathrm{.}97,1\mathrm{.}00],[4,1\mathrm{.}22,0\mathrm{.}97]]$

$\backslash$table$[[$Week$,\backslash$table$[[$Forecast$],[$Method $2]],\backslash$table$[[$Actual$],[$Demand$]]],[1,0\mathrm{.}82,0\mathrm{.}72],[2,1\mathrm{.}19,1\mathrm{.}05],[3,0\mathrm{.}90,1\mathrm{.}00],[4,1\mathrm{.}17,0\mathrm{.}97]]$

The MAD for Method $1=$ thousand gallons $($round your response to three decimal places$).$

The mean squared error $($MSE$)$ for Method $1=$ thousand gallons ${?}^2($round your response to three decimal places$).$

The MAD for Method $2=$ thousand gallons $($round your response to three decimal places$).$

The mean squared error $($MSE$)$ for Method $2=$ thousand gallons ${?}^2($round your response to three decimal places$).$