# How can I add noise to linear graph

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lucky_ el 21 de En. de 2016
Comentada: jgg el 21 de En. de 2016
I have 100 sample points and I'm using y=mx+c to create 1d line and add gaussian noise using randn the attached graph is the result that I got when I tried the first code and when I try the second code I get straight line I think there is something wrong with my plot but I'm not sure where ?
code1
sample = 100;
x = linspace(-5,5);
y= 1.6 * x +6;
dataset = randn(sample,2);
figure
plot(dataset,y)
axis([-8 7])
code2
sample = 100;
x = linspace(-5,5);
y= 1.6 * x +6;
dataset = y*randn(sample,2);
figure
plot(dataset)
axis([-8 7]);
this is the result that I want to get
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jgg el 21 de En. de 2016
Editada: jgg el 21 de En. de 2016
sample = 100;
x = linspace(-5,5);
y= 1.6 * x +6;
r = randn(2,sample);
figure
plot(x,r(1,:)+y)
hold on
plot(x,r(2,:)+y)
The actual outcome value is y + r(i,:) not just y; you also are plotting it incorrectly before.
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lucky_ el 21 de En. de 2016
Thanks that worked I'm still new to this so I wasn't sure .. is there function to plot fitted line
jgg el 21 de En. de 2016
Yes. Let's code it up a little more clearly since you want to fit something too:
sample = 100;
x = linspace(-5,5);
y= 1.6 * x +6;
r = randn(2,sample);
y_noise = y + r(1,:);
X = [ones(1,length(x)); x];
beta = regress(y_noise',X');
y_fitted = beta(1) + x*beta(2);
figure
plot(x,y_noise)
hold on
plot(x,y_fitted)
This fits a linear regression curve to the noisy data using the regress function with an intercept. The coefficients are in beta.

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