Regression2

# Regression2 - assuming that the determined equation is for...

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Sample x y xy x^2 d d^2 1 1 1.2 1.2 1 0.0600 0.0036 2 2 2.1 4.2 4 -0.0800 0.0064 3 3 3.2 9.6 9 -0.0200 0.0004 4 4 4.3 17.2 16 0.0400 0.0016 5 0 6 n= 10.0000 10.8000 32.2000 30.0000 0.0000 0.0120 4 D= s(y)= 20 0.0775 m= s(m)=   1.0400 0.0346 b= s(b)= 0.1000 0.0949 Propagation of uncertainty calculation for calibration curve Measured y= Derived x= u(x)= 2.72 2.5192 0.08327 This program can be used for linear regression. In cells B2 to B7 enter up to 6 x-values   and in cells C2 to C7 enter the corresponding y-values. The program calculates the slope   and y-intercept for y = mx + b. It also calculates the standard deviations for y, m, and b.  This gives uncertainties for the equation,  y +/- s(y) = (m +/- m(y))x + b +/- s(b.) The lower part of the program, gives calculations for a value of x from a measured value of y

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Unformatted text preview: assuming that the determined equation is for a calibration curve. Replace the measured y of 2.72 with any value of y of interest. The uncertainty in the derived x is also calculated as u(x). Select the tab for "Chart 2" below to see the graph for the above line. For details of these calculations, see the reference below. Harris, D.C., Quantitative Chemical Analysis, 4th ed, Freeman, New York, 1995, 81. 0.5 1 1.5 2 2.5 3 3.5 4 4.5 0.5 1 1.5 2 2.5 3 3.5 4 4.5 5 f(x) = 1.04x + 0.1 R² = 0.9977859779 LeastSquaresWithU Column C Linear Regression for Column C...
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