Following are two week frecasts made by two different methods for the number of gallons of gasoline, in thousands, demanded at a local gasoline station Also shown are actual demand in thousands of gallons:

$\backslash$table$[[$Week$,\backslash$table$[[$Forecast$],[$Method $1]],\backslash$table$[[$Actual$],[$Demand$]]],[1,0\mathrm{.}85,0\mathrm{.}68],[2,1\mathrm{.}08,0\mathrm{.}98],[3,0\mathrm{.}92,1\mathrm{.}00],[4\mathrm{.}17,0\mathrm{.}97,]]$

$\backslash$table$[[$Week$,\backslash$table$[[$Forecast$],[$Method $2]],\backslash$table$[[$Actual$],[$Demand$]]],[1,0\mathrm{.}82,0\mathrm{.}68],[2,1\mathrm{.}20,0\mathrm{.}98],[3,0\mathrm{.}90,1\mathrm{.}00],[4,1\mathrm{.}11,0\mathrm{.}97]]$

The MAD for Method $1=0\mathrm{.}138$ 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 $2=0\mathrm{.}150$ thousand gallons $($round your response to three decimal places$)$

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