Following are two weekly forecasts 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 levels, imthousands of gallons:

$\backslash$table$[[$Week$,\backslash$table$[[$Forecast$],[$Method $1]],\backslash$table$[[$Actual$],[$Demand$]]],[1,0\mathrm{.}85,0\mathrm{.}70],[2,1\mathrm{.}05,0\mathrm{.}98],[3,0\mathrm{.}95,0\mathrm{.}96],[4,1\mathrm{.}17,1\mathrm{.}04]]$

$\backslash$table$[[$Week$,\backslash$table$[[$Forecast$],[$Method $2]],\backslash$table$[[$Actual$],[$Demand$]]],[1,0\mathrm{.}77,0\mathrm{.}70],[2,1\mathrm{.}21,0\mathrm{.}98],[3,0\mathrm{.}92,0\mathrm{.}96],[4,1\mathrm{.}15,1\mathrm{.}04]]$

The MAD for Method $1=0\mathrm{.}09$ thousand gallons $($round your response to three decimal places$)$

The mean squared error $($MSE$)$ for Method $1=0\mathrm{.}009$ thousand gallons ${?}^2($round your response to three decimal places$)$

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