Question

csn i get the m file for mathlab plz

QUESTION #2 ture-conductivity data in Table 1 is from a material that is known to follow Arrhenius The temperat law: -1000 S Аевт Perform a least squares regression analysis to find the best-fit values for A and B. Find also the R'value, where B T S-S Plot a graph to show the data points together with the best-fit curve. o wrse Save your main m-file: 02_studentID.m Write the program such that when executed, only the final answers and plots are displayed. If you use a function file, title it '02_studentID _F.m' On the Ist line of each m-file, type % Student ID, Q2 20 POINTS Table 1 applies to Questions 2 and 3. 250 2.7 298 3.6 260 2.9 273 3.2 300 3.8 280 290 3.1 4.0 3.7 QUESTION #2 The temperature-conductivity data in Table 1 is from a material that is known to follow Arrhenius law: -1000 S-Ae BT Perform a least squares regression analysis to find the best-fit values for A and B. Find also the R' value, where S-s S-S Plot a graph to show the data points together with the best-fit curve.

Answer 1

MATLAB Code:

close all
clear
clc

T = [250 260 270 273 280 290 298 300 310]';
S = [2.7 2.9 3.1 3.2 3.4 3.6 3.7 3.8 4.0]';

% S = A*exp(-1000/(B*T))
% => ln(S) = ln(A) - (1000/B)*(1/T)
P = [ones(size(T)) 1./T];
C = P\log(S);

% ln(A) = C(1)
A = exp(C(1));

% -1000/B = C(2)
B = -1000/C(2);
fprintf('Model: S = %.4f * exp(-1000 / (%.4f * T))\n', A, B)

TT = min(T)-10:1:max(T)+10;
plot(T,S,'o',TT,A*exp(-1000./(B*TT)))
title('Least Squares Fit'), xlabel('T'), ylabel('S')
legend('Data Points', 'Least Squares Fit', 'Location', 'northwest')

R2 = 1 - sum((S - (A * exp(-1000 ./ (B*T)))).^2) / sum((S - sum(S)/length(S)).^2);
fprintf('R-Squared Value: %.8f\n', R2)

Output:

Model: S = 20.9337 * exp(-1000 / (1.9501 * T))
R-Squared Value: 0.99569270

Plot:

Least Squares Fit 4.4 O Data Points 4.2 Least Squares Fit 4 3.8 3.6 CD 3.4 3.2 2.8 2.6 2.4 240 250 260 270 280 290 300 310 320