modeling data with a power law In the following, X and Y represent data that needs to be modeled as Y=aXm, where m can be negative or positive, and a>0. Y contains noise, so we need to use least square interpolation. Using the supplied data, calculate a and m for the power law that best fit the data. In the solution submitted via Gradescope explain the choice for the variable transformation that you decided to use. Function 12345function[a,m]=interpSpectra(x,y)oxandyarevectorscontainingthepointstobeinterpolatedyaccordingtoy=axmend