How Do You Relate Fitted Curve to Mean, Standard Deviation, and Standard Error?

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The discussion revolves around relating fitted curve data to statistical measures such as mean, standard deviation, and standard error. The user calculates the mean and standard deviation of the generated data but struggles to understand how to connect these values to the fitted curve. There is confusion regarding the relationship between the fitted curve and the 95% point on the normal distribution's integral. The user seeks clarification on how to interpret and relate these statistical concepts effectively. Overall, the thread highlights a need for a deeper understanding of statistical relationships in data analysis.
coffeem
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Homework Statement



Given:

clear
n = 100;
x = 1:n;
err = randn(1,n);
mean(err);
std(err);
y = x + err;
cftool

Q - Relate your fitted to the data in y to the mean, S and SE values. You should also compare the fit results to the 95% point on the curve of the integral of the normal distribution.


2. The attempt at a solution

I did the following:

Mean = mean(y)

Standard_Deviation = std(y)

Standard_Error = ((Standard_Deviation).^2)./sqrt(100)


But in all honestly don't know what I have to do. I mean how do I relate the data? I think the problem here is that I do not understand the question. Thanks
 
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