A spreadsheet "viscosity.xIsx" contains some data relating the dynamic viscosity of water $(\frac{N**s}{m^2})$ to temperature $T(C).$

Load in the data using readmatrix$().$

Use the fit$()$ command $($and any necessary postprocessing commands$)$ to fit a second$-$order polynomial $($parabola$)$ to the data in the form of:

$(T)=a_1{T}^2+a_{2}T+a_3$

Using this regression, predict $({}_{\text{e}\text{v}\text{a}\text{l}})$ at an arbitrary value of $T(T_{\text{e}\text{v}\text{a}\text{l}}).$ Also output the $R^2$ value.

Generate a properly labeled plot of the data $($including $(T_{\text{e}\text{v}\text{a}\text{l}},{}_{\text{e}\text{v}\text{a}\text{l}}))$ and the best$-$fit curve in your function. The fplot$()$ command may be helpful.