Error Propagation When Dividing By A Constant
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or more quantities, each with their individual uncertainties, and then combine the information from these quantities in order to come up with a final result of our experiment. How can you state your answer for the combined result
Error Propagation When Multiplying By A Constant
of these measurements and their uncertainties scientifically? The answer to this fairly common question propagation of error division by constant depends on how the individual measurements are combined in the result. We will treat each case separately: Addition of measured
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quantities If you have measured values for the quantities X, Y, and Z, with uncertainties dX, dY, and dZ, and your final result, R, is the sum or difference of these quantities, then the uncertainty error propagation addition dR is: Here the upper equation is an approximation that can also serve as an upper bound for the error. Please note that the rule is the same for addition and subtraction of quantities. Example: Suppose we have measured the starting position as x1 = 9.3+-0.2 m and the finishing position as x2 = 14.4+-0.3 m. Then the displacement is: Dx = x2-x1 = 14.4 m - 9.3 error propagation multiplication division m = 5.1 m and the error in the displacement is: (0.22 + 0.32)1/2 m = 0.36 m Multiplication of measured quantities In the same way as for sums and differences, we can also state the result for the case of multiplication and division: Again the upper line is an approximation and the lower line is the exact result for independent random uncertainties in the individual variables. And again please note that for the purpose of error calculation there is no difference between multiplication and division. Example: We have measured a displacement of x = 5.1+-0.4 m during a time of t = 0.4+-0.1 s. What is the average velocity and the error in the average velocity? v = x / t = 5.1 m / 0.4 s = 12.75 m/s and the uncertainty in the velocity is: dv = |v| [ (dx/x)2 + (dt/t)2 ]1/2 = 12.75 m/s [(0.4/5.1)2 + (0.1/0.4)2]1/2 = 3.34 m/s Multiplication with a constant What if you have measured the uncertainty in an observable X, and you need to multiply it with a constant that is known exactly? What is the error then? This is easy: just multiply the error in X with the absolute value of t
find that the error in this measurement is 0.001 in. To find the area we multiply the width (W) and length (L). The area then is L x
Uncertainty Propagation Division
W = (1.001 in) x (1.001 in) = 1.002001 in2 which rounds to 1.002 error propagation multiplication in2. This gives an error of 0.002 if we were given that the square was exactly super-accurate 1 inch a
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side. This is an example of correlated error (or non-independent error) since the error in L and W are the same. The error in L is correlated with that of in W. Now, http://lectureonline.cl.msu.edu/~mmp/labs/error/e2.htm suppose that we made independent determination of the width and length separately with an error of 0.001 in each. In this case where two independent measurements are performed the errors are independent or uncorrelated. Therefore the error in the result (area) is calculated differently as follows (rule 1 below). First, find the relative error (error/quantity) in each of the quantities that enter to the calculation, relative error in http://www.utm.edu/~cerkal/Lect4.html width is 0.001/1.001 = 0.00099900. The resultant relative error is Relative Error in area = Therefore the absolute error is (relative error) x (quantity) = 0.0014128 x 1.002001=0.001415627. which rounds to 0.001. Therefore the area is 1.002 in2± 0.001in.2. This shows that random relative errors do not simply add arithmetically, rather, they combine by root-mean-square sum rule (Pythagorean theorem). Let’s summarize some of the rules that applies to combining error when adding (or subtracting), multiplying (or dividing) various quantities. This topic is also known as error propagation. 2. Error propagation for special cases: Let σx denote error in a quantity x. Further assume that two quantities x and y and their errors σx and σy are measured independently. In this case relative and percent errors are defined as Relative error = σx / x, Percent error = 100 (σx / x) Multiplying or dividing with a constant. The resultant absolute error also is multiplied or divided. Multiplication or division, relative error. Addition or subtraction: In this case, the absolute errors obey Pythagorean theorem. If a and b are constants, If there are more than two measured quantities, you can extend
WorkSocial MediaSoftwareProgrammingWeb Design & DevelopmentBusinessCareersComputers Online Courses B2B Solutions Shop for Books San Francisco, CA Brr, it´s cold outside Search Submit Learn more with dummies Enter your email to http://www.dummies.com/education/science/biology/simple-error-propagation-formulas-for-simple-expressions/ join our mailing list for FREE content right to your inbox. Easy! Your email Submit RELATED ARTICLES Simple Error Propagation Formulas for Simple Expressions Key Concepts in Human Biology and Physiology Chronic Pain and Individual Differences in Pain Perception Pain-Free and Hating It: Peripheral Neuropathy Neurotransmitters That Reduce or Block Pain Load error propagation more EducationScienceBiologySimple Error Propagation Formulas for Simple Expressions Simple Error Propagation Formulas for Simple Expressions Related Book Biostatistics For Dummies By John Pezzullo Even though some general error-propagation formulas are very complicated, the rules for propagating SEs through some simple mathematical expressions are much easier to work with. Here are some of error propagation when the most common simple rules. All the rules that involve two or more variables assume that those variables have been measured independently; they shouldn't be applied when the two variables have been calculated from the same raw data. Adding or subtracting a constant doesn't change the SE Adding (or subtracting) an exactly known numerical constant (that has no SE at all) doesn't affect the SE of a number. So if x = 38 ± 2, then x + 100 = 138 ± 2. Likewise, if x = 38 ± 2, then x - 15 = 23 ± 2. Multiplying (or dividing) by a constant multiplies (or divides) the SE by the same amount Multiplying a number by an exactly known constant multiplies the SE by that same constant. This situation arises when converting units of measure. For example, to convert a length from meters to centimeters, you multiply by exactly 100, so a
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