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, in thousands of gallons:

$\backslash$table$[[$Week$,\backslash$table$[[$Forecast$],[$Method $1]],\backslash$table$[[$Actual$],[$Demand$]],$Week,$\backslash$table$[[$Forecast$],[$Method $2]],\backslash$table$[[$Actual$],[$Demand$]]],[1,0\mathrm{.}85,0\mathrm{.}72,1,0\mathrm{.}80,0\mathrm{.}72],[2,1\mathrm{.}08,1\mathrm{.}05,2,1\mathrm{.}19,1\mathrm{.}05],[3,0\mathrm{.}95,1\mathrm{.}07,3,0\mathrm{.}88,1\mathrm{.}07],[4,1\mathrm{.}22,1\mathrm{.}04,4,1\mathrm{.}15,1\mathrm{.}04]]$

The MAD for Method $1=0\mathrm{.}115$ 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$).$