Absolute Error And Relative Error In Statistics
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as percent (fraction x 100, e.g. 56.2%), as parts per
Absolute Error And Relative Error Examples
thousand (fraction x 1000, e.g. 562 ppt), or as parts per million (fraction x 106 , define absolute error and relative error e.g. 562,000 ppm). Absolute Accuracy Error Example: 25.13 mL - 25.00 mL = +0.13 mL absolute error Relative Accuracy Error Example: (( 25.13 mL - 25.00 mL)/25.00 mL) x 100% how to find absolute error and relative error = 0.52% relative error. Example: For professional gravimetric chloride results we must have less than 0.2% relative error. Absolute Precision Error standard deviation of a set of measurements: standard deviation of a value read from a working curve Example: The standard deviation of 53.15 %Cl, 53.56 %Cl, and 53.11 %Cl is 0.249 %Cl absolute uncertainty. Relative Precision Error Relative Standard Deviation (RSD) Coefficient of Variation (CV) Example: The CV of 53.15 %Cl, 53.56 %Cl, and 53.11 %Cl is (0.249 %Cl/53.27 %Cl)x100% = 0.47% relative uncertainty. David L. Zellmer Chem 102 February 9, 1999
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Absolute Error Calculation
Learn more about hiring developers or posting ads with us Mathematics Questions Tags Users Badges absolute error and relative error in numerical analysis Unanswered Ask Question _ Mathematics Stack Exchange is a question and answer site for people studying math at any level and professionals
Difference Between Absolute And Relative Error
in related fields. Join them; it only takes a minute: Sign up Here's how it works: Anybody can ask a question Anybody can answer The best answers are voted up and rise to the top How to http://zimmer.csufresno.edu/~davidz/Chem102/Gallery/AbsRel/AbsRel.html calculate relative error when true value is zero? up vote 10 down vote favorite 3 How do I calculate relative error when the true value is zero? Say I have $x_{true} = 0$ and $x_{test}$. If I define relative error as: $\text{relative error} = \frac{x_{true}-x_{test}}{x_{true}}$ Then the relative error is always undefined. If instead I use the definition: $\text{relative error} = \frac{x_{true}-x_{test}}{x_{test}}$ Then the relative error is always 100%. Both methods seem useless. Is there http://math.stackexchange.com/questions/677852/how-to-calculate-relative-error-when-true-value-is-zero another alternative? statistics share|cite|improve this question asked Feb 15 '14 at 22:41 okj 941818 1 you need a maximum for that.. –Seyhmus Güngören Feb 15 '14 at 23:06 1 Simple and interesting question, indeed. Could you tell in which context you face this situation ? Depending on your answer, there are possible alternatives. –Claude Leibovici Feb 16 '14 at 6:24 1 @ClaudeLeibovici: I am doing a parameter estimation problem. I know the true parameter value ($x_{true}$), and I have simulation data from which I infer an estimate of the parameter ($x_{test}$). I want to quantify the error, and it seems that for my particular case relative error is more meaningful than absolute error. –okj Feb 17 '14 at 14:05 1 What about $\text{error} = 2 \frac{x_{true}-x_{test}}{x_{true}+x_{test}}$ if it is for an a posteriori analysis ? –Claude Leibovici Feb 17 '14 at 14:16 1 @okj. I am familiar with this situation. Either use the classical relative error and return $NaN$ if $x_{true}=0$ either adopt this small thing. It is always the same problem with that. You also can add a translation to the $x$'s to get rid of this. –Claude Leibovici Feb 17 '14 at 15:40 | show 4 more comments 4 Answers 4 active oldest votes up vote 5 down vote accepted First of all, le
The difference between two measurements is called a variation in the measurements. Another word for this variation - or uncertainty in measurement - is "error." This "error" is not the same as a "mistake." It does not mean that you got http://www.regentsprep.org/regents/math/algebra/am3/LError.htm the wrong answer. The error in measurement is a mathematical way to show the uncertainty in the measurement. It is the difference between the result of the measurement and the true value of what you were measuring. The precision of a measuring instrument is determined by the smallest unit to which it can measure. The precision is said to be the same as the smallest fractional or decimal division on the scale of the measuring instrument. Ways of Expressing absolute error Error in Measurement: 1. Greatest Possible Error: Because no measurement is exact, measurements are always made to the "nearest something", whether it is stated or not. The greatest possible error when measuring is considered to be one half of that measuring unit. For example, you measure a length to be 3.4 cm. Since the measurement was made to the nearest tenth, the greatest possible error will be half of one tenth, or 0.05. 2. Tolerance intervals: Error in measurement and relative error may be represented by a tolerance interval (margin of error). Machines used in manufacturing often set tolerance intervals, or ranges in which product measurements will be tolerated or accepted before they are considered flawed. To determine the tolerance interval in a measurement, add and subtract one-half of the precision of the measuring instrument to the measurement. For example, if a measurement made with a metric ruler is 5.6 cm and the ruler has a precision of 0.1 cm, then the tolerance interval in this measurement is 5.6 0.05 cm, or from 5.55 cm to 5.65 cm. Any measurements within this range are "tolerated" or perceived as correct. Accuracy is a measure of how close the result of the measurement comes to the "true", "actual", or "accepted" value. (How close is your answer to the accepted value?) Tolerance is the greatest range of variation that can be allowed. (How much error in the answer is occurring or is acceptable?) 3. Absolute Error and Relative Error: Error in measurement may be represented by the actual amount of error, or by a ratio comparing the error to the size of the measurement. The absolute error of the measurement shows how large the error actually is, while the relative error of the measurement shows how large the error is in relation to the correct value. Absolute errors do not always give an indication of how important the error may be. If y
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