create best fit line for this data: hs = [0 .5 .75 1 1.1 1.7 2 2.5 3.1 3.6 4 4.6 5.1 5.2 5.8 6.1 6.4 6.5]; grade = [30 35 38 42 47 50 55 58 61 68 77 80 83 84 89 94 92 98]; in matlab

main.m
% Data
hs = [0, 0.5, 0.75, 1, 1.1, 1.7, 2, 2.5, 3.1, 3.6, 4, 4.6, 5.1, 5.2, 5.8, 6.1, 6.4, 6.5];  
grade = [30, 35, 38, 42, 47, 50, 55, 58, 61, 68, 77, 80, 83, 84, 89, 94, 92, 98];  

% Fit a polynomial regression line
p = polyfit(hs, grade, 1);  % linear regression (degree 1 polynomial)
f = polyval(p, hs);

% Plot
scatter(hs, grade, 'b'); % scatter plot
hold on
plot(hs, f, 'r'); % fitted line
hold off

% Display the equation of the best fit line
fprintf('The best fit line equation is: y = %.2fx + %.2f\n', p(1), p(2));
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