Propagation Of Error Approach
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The approach to uncertainty analysis that has been followed up to this point in the discussion has been what is called a top-down approach. Uncertainty components are estimated from direct repetitions of the measurement result. To contrast this with a propagation of error division propagation of error approach, consider the simple example where we estimate the area of
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a rectangle from replicate measurements of length and width. The area $$ area = length \cdot width $$ can be error propagation chemistry computed from each replicate. The standard deviation of the reported area is estimated directly from the replicates of area. Advantages of top-down approach This approach has the following advantages: proper treatment of covariances error propagation excel between measurements of length and width proper treatment of unsuspected sources of error that would emerge if measurements covered a range of operating conditions and a sufficiently long time period independence from propagation of error model Propagation of error approach combines estimates from individual auxiliary measurements The formal propagation of error approach is to compute: standard deviation from the length measurements standard deviation from the width measurements and
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combine the two into a standard deviation for area using the approximation for products of two variables (ignoring a possible covariance between length and width), $$ s_{area} = \sqrt{width^2 \cdot s_{length}^2 + length^2 \cdot s_{width}^2} $$ Exact formula Goodman (1960) derived an exact formula for the variance between two products. Given two random variables, \(x\) and \(y\) (correspond to width and length in the above approximate formula), the exact formula for the variance is: $$ V(\bar{x} \bar{y}) = \frac{1}{n} \left[ X^2 V(y) + Y^2 V(x) + 2XYE_{11} + 2X\frac{E_{12}}{n} + 2Y\frac{E_{21}}{n} + \frac{V(x) V(y)}{n} + \frac{Cov((\Delta x)^2, (\Delta y)^2) -E_{11}^2 }{n^2} \right] $$ with \(X = E(x)\) and \(Y = E(y)\) (corresponds to width and length, respectively, in the approximate formula) \(V(x)\) is the variance of \(x\) and \(V(y)\) is the variance \(y\) (corresponds to \(s^2\) for width and length, respectively, in the approximate formula) \( E_{ij} = {(\Delta x)^i, (\Delta y)^j}\) where \( \Delta x = x - X \) and \( \Delta y = y - Y \) \( Cov((\Delta x)^2, (\Delta y)^2) = E_{22} - V(x) V(y) \) To obtain the standard deviation, simply take the square root of the above formula. Also, an estimate of
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of Error Last updated 20:33, 14 May 2016 Save as PDF Share Share Share Tweet Share IntroductionDerivation of Exact FormulaDerivation of Arithmetic ExampleCaveats and WarningsDisadvantages of Propagation of Error http://www.itl.nist.gov/div898/handbook/mpc/section5/mpc55.htm ApproachTreatment of Covariance TermsReferencesContributors Propagation of Error (or Propagation of Uncertainty) is defined as the effects on a function by a variable's uncertainty. It is a calculus derived statistical calculation designed to combine uncertainties from multiple variables, in order to provide an accurate measurement of uncertainty. Introduction Every measurement has an air of uncertainty about it, and not http://chem.libretexts.org/Core/Analytical_Chemistry/Quantifying_Nature/Significant_Digits/Propagation_of_Error all uncertainties are equal. Therefore, the ability to properly combine uncertainties from different measurements is crucial. Uncertainty in measurement comes about in a variety of ways: instrument variability, different observers, sample differences, time of day, etc. Typically, error is given by the standard deviation (\(\sigma_x\)) of a measurement. Anytime a calculation requires more than one variable to solve, propagation of error is necessary to properly determine the uncertainty. For example, lets say we are using a UV-Vis Spectrophotometer to determine the molar absorptivity of a molecule via Beer's Law: A = ε l c. Since at least two of the variables have an uncertainty based on the equipment used, a propagation of error formula must be applied to measure a more exact uncertainty of the molar absorptivity. This example will be continued below, after the derivation (see Example Calculation). Derivation of Exact Formula Suppose a certain experiment requires multiple instruments to carry out. These instruments each have different variability in their measurements. The results of each instrument are given as: a, b, c, d..
Επιλέξτε τη γλώσσα σας. Κλείσιμο Μάθετε περισσότερα View this message in English Το YouTube εμφανίζεται στα https://www.youtube.com/watch?v=N0OYaG6a51w Ελληνικά. Μπορείτε να αλλάξετε αυτή την προτίμηση παρακάτω. Learn more You're viewing YouTube in Greek. You can change this preference below. Κλείσιμο Ναι, θέλω να τη κρατήσω Αναίρεση Κλείσιμο Αυτό error propagation το βίντεο δεν είναι διαθέσιμο. Ουρά παρακολούθησηςΟυράΟυρά παρακολούθησηςΟυρά Κατάργηση όλωνΑποσύνδεση Φόρτωση... Ουρά παρακολούθησης Ουρά __count__/__total__ Calculating the Propagation of Uncertainty Scott Lawson ΕγγραφήΕγγραφήκατεΚατάργηση εγγραφής3.7133 χιλ. Φόρτωση... Φόρτωση... Σε λειτουργία... Προσθήκη σε... Θέλετε propagation of error να το δείτε ξανά αργότερα; Συνδεθείτε για να προσθέσετε το βίντεο σε playlist. Σύνδεση Κοινή χρήση Περισσότερα Αναφορά Θέλετε να αναφέρετε το βίντεο; Συνδεθείτε για να αναφέρετε ακατάλληλο περιεχόμενο. Σύνδεση Μεταγραφή Στατιστικά στοιχεία 48.416 προβολές 182 Σας αρέσει αυτό το βίντεο; Συνδεθείτε για να μετρήσει η άποψή σας. Σύνδεση 183 11 Δεν σας αρέσει αυτό το βίντεο; Συνδεθείτε για να μετρήσει η άποψή σας. Σύνδεση 12 Φόρτωση... Φόρτωση... Μεταγραφή Δεν ήταν δυνατή η φόρτωση της διαδραστικής μεταγραφής. Φόρτωση... Φόρτωση... Η δυνατότητα αξιολόγησης είναι διαθέσιμη όταν το βίντεο είναι ενοικ