Flag = 1 or 2 or 3 1: 2: 3: [a1, a2, Ea1, Ea2, r] = linear_fit(xyData, xmin, xmax, flag) coefficients x i, y i data in a matrix of n rows by 2 columns.

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Presentation transcript:

Flag = 1 or 2 or 3 1: 2: 3: [a1, a2, Ea1, Ea2, r] = linear_fit(xyData, xmin, xmax, flag) coefficients x i, y i data in a matrix of n rows by 2 columns Column 1: x i data Column 2: y i data max x value for plot min x value for plot uncertainties correlation coefficient

[area, prob, FWHM, xFWHM1, xFWHM2] = gauss(mu, sigma, x1, x2) Outputs Total area under curve (%) Probability (%) Full Width at Half Maximum and corresponding x values mean Standard deviation Limits for probability calculation Inputs

prob = chi2test(dof, chi2Max) Outputs Probability  2 >  2 max Value of  2 to test Degrees of freedom Inputs

[n, xbar, mode, median, s_pop, s_sample, E] = stat(StatData) Outputs Number of measurements Inputs Mean Mode Median Sample standard deviation Population standard deviation Standard error of the mean Measurements: Frequency Value