What am I doing wrong here? I Keep getting "All table variables must have the same number of rows." error.

data = load('therm_con.dat.dat');
temperature = data(:, 1);
conductivity = data(:, 2);
% Define the model equations
equation1 = @(c, T) 1 ./ (c(1)./T + c(2)*T.^2);
equation2 = @(c, T) 1 ./ (c(1)./T + c(2)*T + c(3)*T.^2);
% Perform curve fitting using GLLS method and Equation 1
c1_eq1_glls = lsqcurvefit(equation1, [1, 1], temperature, conductivity);
fit_eq1_glls = equation1(c1_eq1_glls, temperature);
% Perform curve fitting using fminsearch method and Equation 1
c1_eq1_fmin = fminsearch(@(c) norm(equation1(c, temperature) - conductivity), [1, 1]);
fit_eq1_fmin = equation1(c1_eq1_fmin, temperature);
% Perform curve fitting using GLLS method and Equation 2
c_eq2_glls = lsqcurvefit(equation2, [1, 1, 1], temperature, conductivity);
fit_eq2_glls = equation2(c_eq2_glls, temperature);
% Perform curve fitting using fminsearch method and Equation 2
c_eq2_fmin = fminsearch(@(c) norm(equation2(c, temperature) - conductivity), [1, 1, 1]);
fit_eq2_fmin = equation2(c_eq2_fmin, temperature);
% Calculate curve fit quantities
S_R_eq1_glls = sum((fit_eq1_glls - conductivity).^2);
S_R_eq1_fmin = sum((fit_eq1_fmin - conductivity).^2);
S_t_eq1_glls = sqrt(S_R_eq1_glls / (length(temperature) - 2));
S_t_eq1_fmin = sqrt(S_R_eq1_fmin / (length(temperature) - 2));
R2_eq1_glls = 1 - S_R_eq1_glls / sum((conductivity - mean(conductivity)).^2);
R2_eq1_fmin = 1 - S_R_eq1_fmin / sum((conductivity - mean(conductivity)).^2);
S_R_eq2_glls = sum((fit_eq2_glls - conductivity).^2);
S_R_eq2_fmin = sum((fit_eq2_fmin - conductivity).^2);
S_t_eq2_glls = sqrt(S_R_eq2_glls / (length(temperature) - 3));
S_t_eq2_fmin = sqrt(S_R_eq2_fmin / (length(temperature) - 3));
R2_eq2_glls = 1 - S_R_eq2_glls / sum((conductivity - mean(conductivity)).^2);
R2_eq2_fmin = 1 - S_R_eq2_fmin / sum((conductivity - mean(conductivity)).^2);
% Generate the plot
figure;
plot(temperature, conductivity, 'bo', 'MarkerSize', 5);
hold on;
plot(temperature, fit_eq1_glls, 'r-', 'LineWidth', 1.5);
plot(temperature, fit_eq1_fmin, 'g--', 'LineWidth', 1.5);
plot(temperature, fit_eq2_glls, 'm-', 'LineWidth', 1.5);
plot(temperature, fit_eq2_fmin, 'c--', 'LineWidth', 1.5);
hold off;
title('Curve Fitting of Thermal Conductivity Data');
xlabel('Temperature (K)');
ylabel('Thermal Conductivity (W/m/K)');
legend('Experimental Data', 'Equation 1 (GLLS)', 'Equation 1 (fminsearch)', 'Equation 2 (GLLS)', 'Equation 2 (fminsearch)');
grid on;
% Generate the tables
methodNames = {'GLLS', 'fminsearch'};
equation1Coefficients = [c1_eq1_glls; c1_eq1_fmin];
equation2Coefficients = [c_eq2_glls; c_eq2_fmin];
standardErrors = [S_t_eq1_glls, S_t_eq1_fmin, S_t_eq2_glls, S_t_eq2_fmin];
rSquaredValues = [R2_eq1_glls, R2_eq1_fmin, R2_eq2_glls, R2_eq2_fmin];
table1 = table(methodNames', standardErrors', rSquaredValues', 'VariableNames', {'Method', 'Standard Error', 'R^2'});
table2 = table(methodNames', equation1Coefficients(:, 1), equation1Coefficients(:, 2), ...
    equation2Coefficients(:, 1), equation2Coefficients(:, 2), equation2Coefficients(:, 3), ...
    'VariableNames', {'Method', 'c1 (Equation 1)', 'c2 (Equation 1)', 'c1 (Equation 2)', 'c2 (Equation 2)', 'c3 (Equation 2)'});
% Display the tables
disp('Table 1:');
disp(table1);
disp('Table 2:');
disp(table2);

Error using table

All table variables must have the same number of rows.

Error in Project_2 (line 62)

table1 = table(methodNames', standardErrors', rSquaredValues', 'VariableNames', {'Method', 'Standard Error', 'R^2'});

Therm_con.dat

12.2900000000000	2535
13.7500000000000	2788
14.8200000000000	2993
16.1200000000000	3042
18.0400000000000	3100
18.6700000000000	3196
20.5200000000000	3247
22.6800000000000	3033
25.1500000000000	3114
27.7200000000000	2746
30.2400000000000	2329
33.2100000000000	2072
36.4800000000000	1724
39.8600000000000	1471
50.4000000000000	950

Answer 1

[Walter Roberson]

methodNames = {'GLLS', 'fminsearch'};

That is a row vector of length 2

standardErrors = [S_t_eq1_glls, S_t_eq1_fmin, S_t_eq2_glls, S_t_eq2_fmin];

Unless there are some empty variables in that list, we can predict that has at least 4 columns.

table1 = table(methodNames', standardErrors', rSquaredValues', 'VariableNames', {'Method', 'Standard Error', 'R^2'});

methodNames is 1 x 2, methodNames' is 2 x 1.

standardErrors is at least N x 4 (N might be 1), standardErrors' is at least 4 x N (N might be 1)

2 rows is not the same number of rows as 4 or more rows.