Use matlab to solve the questions 28. Write a user-defined function that determines the best fit of an exponentialfunction of the form y=be. NameName the function [b, m]expofit (x, y), where the input arguments x and y are vectors with thecoordinates of the data points, and the output arguments b and m are theconstants of the fitted exponential equation. Use expofit to fit the databelow. Make a plot that shows the data points and the function.XT (K)k (W/m-K)T (K)k (W/m-K)y2460.41.729. Estimated values of thermal conductivity of silicon at different temperaturesare given in the following table.8042.210.161007.63.15.0 6.626.9 61.2 158 398815010300 820 1,560 2,300 5,00020250 350403,500500 1,0001,350 900400 190 1207530(a) Make a plot of k versus T using log scale on both axes.(b) Curve-fit the data with a second-order polynomial y = ax² +bx+c inwhich x=log(T) and y=log(k). Once the coefficients a, b, and c aredetermined, write an equation for k as a function of log(T). Use thisequation for curve-fitting the data. Make a second plot that shows thedata points with markers and the curve-fitted equation with a solid line.(c) Repeat part (b) using a third-order polynomial.602,100=1,40020

Start.Define data points for an exponential fit: x1 and y1.Use the expofit function to find…

28. Write a user-defined function that determines the best fit of an exponential function of the form y=be. Name the function [b, m] expofit (x, y), where the input arguments x and y are vectors with the coordinates of the data points, and the output arguments b and m are the constants of the fitted exponential equation. Use expofit to fit the data below. Make a plot that shows the data points and the function. X T (K) k (W/m-K) T (K) k (W/m-K) y 2 0.4 1.7 29. Estimated values of thermal conductivity of silicon at different temperatures are given in the following table. 46 2.2 10.1 4 6 300 820 3.1 5.0 6.6 7.6 26.9 61.2 158 398 150 8 10 20 1,560 2,300 250 350 500 40 5,000 3,500 2,100 1,000 1,400 60 80 100 1,350 900 400 190 120 75 (a) Make a plot of k versus T using log scale on both axes. (b) Curve-fit the data with a second-order polynomial y=ax²+bx+c in which x=log(T) and y=log(k). Once the coefficients a, b, and c are determined, write an equation for k as a function of log(7) . Use this equation for curve-fitting the data. Make a second plot that shows the data points with markers and the curve-fitted equation with a solid line. (c) Repeat part (b) using a third-order polynomial. 30 20