I have data in two collumns. collumn A is X and collumn B is Y.

I interpolated some x(lower case now) values so that the data given from X would be separated evenly through the axis (as it was not previously).

I then fitted a

Now I have a problem. I need to run a goodness-of-fit test and I need to compare the raw data with the new smoothed data.

Does anyone know how, on MathCad, to interpolate some y-axis values, y, so that it (the raw data) is comparable with the newly smoothed data in a goodness-of-fit test?

Or does anyone have an alternate way getting a goodness-of-fit test without having to interpolate new values?

Thanks in advance,

Niste

I interpolated some x(lower case now) values so that the data given from X would be separated evenly through the axis (as it was not previously).

I then fitted a

**fit(x):=cspline(S,X,Y,x)**function to smooth the raw data.Now I have a problem. I need to run a goodness-of-fit test and I need to compare the raw data with the new smoothed data.

Does anyone know how, on MathCad, to interpolate some y-axis values, y, so that it (the raw data) is comparable with the newly smoothed data in a goodness-of-fit test?

Or does anyone have an alternate way getting a goodness-of-fit test without having to interpolate new values?

Thanks in advance,

Niste

**EDIT:**

Sorry that was really confusing. All I want to know is:- if i've interpolated some new x points for a new function f(x), how do I interpolate the same number of points in the original y data so it can be comparable with the new function?Sorry that was really confusing. All I want to know is:- if i've interpolated some new x points for a new function f(x), how do I interpolate the same number of points in the original y data so it can be comparable with the new function?

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