Percent Error Of Mean
the quantity being forecast. The formula for the mean percentage error is MPE = 100 % n ∑ t = 1 n a t − f t a t {\displaystyle {\text{MPE}}={\frac {100\%}{n}}\sum _{t=1}^{n}{\frac {a_{t}-f_{t}}{a_{t}}}} where at is the actual value of the quantity being forecast, ft is the forecast, and n is the number of different times for which the variable is forecast. Because actual rather than absolute values of the forecast errors are used in the formula, positive and negative forecast errors can offset each other; as a result the formula can be used as a measure of the bias in the forecasts. A disadvantage of this measure is that it is undefined whenever a single actual value is zero. See also[edit] Percentage error Mean absolute percentage error Mean squared error Mean squared prediction error Minimum mean-square error Squared deviations Peak signal-to-noise ratio Root mean square deviation Errors and residuals in statistics References[edit] Khan, Aman U.; Hildreth, W. Bartley (2003). Case studies in public budgeting and financial management. New York, N.Y: Marcel Dekker. ISBN0-8247-0888-1. Waller, Derek J. (2003). Operations Management: A Supply Chain Approach. Cengage Learning Business Press. ISBN1-86152-803-5. Retrieved from "https://en.wikipedia.org/w/index.php?title=Mean_percentage_error&oldid=723517980" Categories: Summary statistics Navigation menu Personal tools Not logged inTalkContributionsCreate accountLog in Namespaces Article Talk Variants Views Read Edit View history More Search Navigation Main pageContentsFeatured contentCurrent eventsRandom articleDonate to WikipediaWikipedia store Interaction HelpAbout WikipediaCommunity portalRecent changesContact page Tools What links hereRelated changesUpload fileSpecial pagesPermanent linkPage informationWikidata itemCite this page Print/export Create a bookDownload as PDFPrintable version Languages Add links This page was last modified on 3 June 2016, at 14:20. Text is available under the Creative Commons Attribution-ShareAlike License; additional terms may apply. By using this site, you agree to the Terms of Use and Privacy Policy. Wikipedia® is a registered trademark of the Wikimedia Foundation, Inc., a non-profit organization. Privacy policy About Wikipedia Disclaimers Contact Wikipedia Developers Cookie statement Mobile view
may be challenged and removed. (December 2009) (Learn how and when to remove this template message) The mean absolute percentage error (MAPE), also known as mean absolute percentage deviation (MAPD), is a measure of prediction accuracy of a forecasting method in statistics, for example in trend estimation. It usually expresses accuracy as a percentage, and is defined by the formula: M = 100 n ∑ t = 1 n | A t − F t A t | , {\displaystyle {\mbox{M}}={\frac {100}{n}}\sum https://en.wikipedia.org/wiki/Mean_percentage_error _{t=1}^{n}\left|{\frac {A_{t}-F_{t}}{A_{t}}}\right|,} where At is the actual value and Ft is the forecast value. The difference between At and Ft is divided by the Actual value At again. The absolute value in this calculation is summed for every forecasted point in time and divided by the number of fitted pointsn. Multiplying by 100 makes it a percentage error. https://en.wikipedia.org/wiki/Mean_absolute_percentage_error Although the concept of MAPE sounds very simple and convincing, it has major drawbacks in practical application [1] It cannot be used if there are zero values (which sometimes happens for example in demand data) because there would be a division by zero. For forecasts which are too low the percentage error cannot exceed 100%, but for forecasts which are too high there is no upper limit to the percentage error. When MAPE is used to compare the accuracy of prediction methods it is biased in that it will systematically select a method whose forecasts are too low. This little-known but serious issue can be overcome by using an accuracy measure based on the ratio of the predicted to actual value (called the Accuracy Ratio), this approach leads to superior statistical properties and leads to predictions which can be interpreted in terms of the geometric mean.[1] Contents 1 Alternative MAPE definitions 2 Issues 3 See also 4 External links 5 References Alternative MAPE definitions[edit] Problems can occur when calculating the
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" http://www.regentsprep.org/regents/math/algebra/am3/LError.htm is not the same as a "mistake." It does not mean that you got the wrong answer. The error in measurement is a mathematical way to show the uncertainty in the measurement. It http://www.wikihow.com/Calculate-Percentage-Error 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 percent error 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 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 percent error of 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 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
this Article Home » Categories » Education and Communications » Subjects » Mathematics » Probability and Statistics ArticleEditDiscuss Edit ArticlewikiHow to Calculate Percentage Error Community Q&A Calculating percentage error allows you to compare an estimate to an exact value. The percentage error gives you the difference between the approximate and exact values as a percentage of the exact value and can help you see how close your guess or estimate was to a real value. If you want to know how to calculate percentage error, all you need to know is the approximate and exact value and you'll be on your way. Steps 1 Know the formula for calculating percentage error. The formula for calculating percentage error is simple:[1]'[(|Exact Value-Approximate Value|)/Exact Value] x 100 The approximate value is the estimated value, and the exact value is the real value. Once you find the absolute value of the difference between the approximate value and exact value, all you need to do is to divide it by the exact value and multiply the result by 100. 2 Subtract the real number from your number. This means that you should subtract the real value from the estimated value. In this case, the real value is 10 and the estimated value is 9. Ex: 10 - 9 = 1 3 Divide the result by the real number. Simply divide -1, the result when 10 is subtracted from 9, by 10, the real value. Place the fraction in decimal form. Ex:-1/10 = -0.1 4 Find the absolute value of the result. The absolute value of a number is the value of the positive value of the number, whether it's positive or negative. The absolute value of a positive number is the number itself and the absolute value of a negative number is simply the value of the number without the negative sign, so the negative number becomes positive. Ex: |-0.1| = 0.1 5 Multiply the result by 100. Simply multiply the result, 0.1, by 100. This will convert the answer into percent form. Just add the percentage symbol to the answer and you're done. Ex: 0.1 x 100 = 10% Community Q&A Search Add New Question How do I calculate a percentage error when resistors are connected in a series? wikiHow Contributor Carry the 2 and get the square root of the previous answer.