# Showing the equation of the best fit lines per graph

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Cody Anderson on 12 Sep 2021
Commented: Cody Anderson on 12 Sep 2021
I am trying to get the equations on the best fit lines to be displayed in the graph, I don't have any idea of how to get it to work. I looked up at few ways but nothing worked for me.
Code:
x = [0.54 0.86 0.99 1.19 1.44 1.76 1.97 2.23 2.44]
y = [1.08 1.71 1.98 2.39 2.89 3.52 3.95 4.45 4.89]
x1 = [0.54 0.86 0.99 1.19 1.44 1.76 1.97 2.23 2.44]
y1 = [0.78 1.18 1.57 1.96 2.35 2.74 3.14 3.53 3.92]
close all
figure(1)
scatter(x1,y1)
p = polyfit(x1,y1,1)
f = polyval(p,x1);
p1 = polyfit(x,y,1)
f2 = polyval(p1,x);
hold on
plot(x1,f,'--r',x,f2,'-b')
title('Force vs mu_0 for Sphereical Cup')
xlabel('mu_0 (N)')
ylabel('Force')
hold on
legend('Experimental values','Best Fit Line','Therotical values')
x3 = [0.47 0.68 1.32 1.76 2.23 2.74 3.16 3.61 4.16 4.53]
y3 = [0.39 0.78 1.18 1.57 1.96 2.35 2.74 3.14 3.53 3.92]
x4 = [0.47 0.68 1.32 1.76 2.23 2.74 3.16 3.61 4.16 4.53]
y4 = [0.47 0.68 1.32 1.76 2.23 2.74 3.16 3.61 4.16 4.53]
figure(2)
scatter(x3,y3)
p = polyfit(x3,y3,3)
f = polyval(p,x3);
p2 = polyfit(x4,y4,1)
f2 = polyval(p2,x4);
hold on
plot(x3,f,'--r',x4,f2,'-b')
title('Force vs mu_0 for Flat Plate')
xlabel('mu_0 (N)')
ylabel('Force')
hold on
legend('Experimental values','Best Fit Line','Theoretical values')

Dave B on 12 Sep 2021
Are you struggling with how to get the text? or how to display it on the chart?
Here I put them in the legend, and also added the cubic equation to the chart with the text function. I chose 2 decimal places but you can consider a different precision as you like.
x3 = [0.47 0.68 1.32 1.76 2.23 2.74 3.16 3.61 4.16 4.53];
y3 = [0.39 0.78 1.18 1.57 1.96 2.35 2.74 3.14 3.53 3.92];
x4 = [0.47 0.68 1.32 1.76 2.23 2.74 3.16 3.61 4.16 4.53];
y4 = [0.47 0.68 1.32 1.76 2.23 2.74 3.16 3.61 4.16 4.53];
scatter(x3,y3)
p = polyfit(x3,y3,3);
f = polyval(p,x3);
p2 = polyfit(x4,y4,1);
f2 = polyval(p2,x4);
hold on
plot(x3,f,'--r',x4,f2,'-b')
title('Force vs mu_0 for Flat Plate')
xlabel('mu_0 (N)')
ylabel('Force')
hold on
eq1 = sprintf('f(x) = %0.2fx^3 + %0.2fx^2 + %0.2fx + %0.2f',p);
eq2 = sprintf('f(x) = %0.2fx + %0.2f',p2);
legend('Experimental values' , ['Best Fit Line: ' eq1], ['Theoretical values: ' eq2])
text(max(xlim),min(ylim),eq1,'VerticalAlignment','bottom','HorizontalAlignment','right','Color','r') Cody Anderson on 12 Sep 2021