Precision is a description of random errors, a measure of statistical variability. Accuracy has two definitions: More commonly, it is a description of systematic errors, a measure of statistical bias; as these cause a difference between a result and a "true" value, ISO calls this trueness. Alternatively, ISO defines accuracy as describing a combination of both types of observational error above (random and systematic), so high accuracy requires both high precision and high trueness. In simplest terms, given a set of data points from repeated measurements of the same quantity, the set can be said to be precise if the values are close to each other, while the set can be said to be accurate if their average is close to the true value of the quantity being measured. The two concepts are independent of each other, so a particular set of data can be said to be either accurate, or precise, or both, or neither. Contents 1 Common definition 1.1 Quantification 2 ISO definition (ISO 5725) 3 In binary classification 4 In psychometrics and psychophysics 5 In logic simulation 6 In information systems 7 See also 8 References 9 External links Common definition[edit] Accuracy is the proximity of measurement results to the true value; precision, the repeatability, or reproducibility of the measurement In the fields of science and engineering, the accuracy of a measurement system is the degree of closeness of measurements of a quantity to that quantity's true value.[1] The precision of a measurement system, related to reproducibility and repeatability, is the degree to which repeated measurements under unchanged conditions show the same results.[1][2] Although the two words precision and accuracy can be synonymous in colloquial use, they are deliberately contrasted in the context of the scientific method. Interestingly, the field of statistics, where the interpretation of measurements plays a central role, prefers to use the terms bias and variability instead of accuracy and precision: bias is the amount of inaccuracy and variability is the amount of imprecision. A measurement system can be accurate but not precise, precise but not accurate, neither, or both. For example, if an experiment contains a systematic error, then increasing the sample size generally increases precision but does not improve accuracy. The result would be a consistent yet inaccurate string of results from the flawed experiment. Eliminating the systematic error improves accuracy but does not change precision. A measurement system is considered valid if it is both accurate and precise. Related terms include bias (nonrandom or directed effects caused by a factor or factors unrelated to the independent variable) and error (random variability). The terminology is also applied to indirect measurements—that is, values obtained by a computational procedure from observed data. In addition to accuracy and precision, measurements may also have a measurement resolution, which is the smallest change in the underlying physical quantity that produces a response in the measurement. In numerical analysis, accuracy is also the nearness of a calculation to the true value; while precision is the resolution of the representation, typically defined by the number of decimal or binary digits. In military terms, accuracy refers primarily to the accuracy of fire (or "justesse de tir"), the precision of fire expressed by the closeness of a grouping of shots at and around the centre of the target.[3] Quantification[edit] See also: False precision In industrial instrumentation, accuracy is the measurement tolerance, or transmission of the instrument and defines the limits of the errors made when the instrument is used in normal operating conditions.[4] Ideally a measurement device is both accurate and precise, with measurements all close to and tightly clustered around the true value. The accuracy and precision of a measurement process is usually established by repeatedly measuring some traceable reference standard. Such standards are defined in the International System of Units (abbreviated SI from French: Système international d'unités) and maintained by national standards organizations such as the National Institute of Standards and Technology in the United States. This also applies when measurements are repeated and averaged. In that case, the term standard error is properly applied: the precision of the average is equal to the known standard deviation of the process divided by the square root of the number of measurements averaged. Further, the central limit theorem shows that the probability distribution of the averaged measurements will be closer to a normal distribution than that of individual measurements. With regard to accuracy we can distinguish: the difference between the mean of the measurements and the reference value, the bias. Establishing and correcting for bias is necessary for calibration. the combined effect of that and precision. A common convention in science and engineering is to express accuracy and/or precision implicitly by means of significant figures. Here, when not explicitly stated, the margin of error is understood to be onehalf the value of the last significant place. For instance, a recording of 843.6 m, or 843.0 m, or 800.0 m would imply a margin of 0.05 m (the last significant place is the tenths place), while a recording of 8436 m would imply a margin of error of 0.5 m (the last significant digits are the units). A reading of 8,000 m, with trailing zeroes and no decimal point, is ambiguous; the trailing zeroes may or may not be intended as significant figures. To avoid this ambiguity, the number could be represented in scientific notation: 8.0 × 103 m indicates that the first zero is significant (hence a margin of 50 m) while 8.000 × 103 m indicates that all three zeroes are significant, giving a margin of 0.5 m. Similarly, it is possible to use a multiple of the basic measurement unit: 8.0 km is equivalent to 8.0 × 103 m. In fact, it indicates a margin of 0.05 km (50 m). However, reliance on this convention can lead to false precision errors when accepting data from sources that do not obey it.[citation needed] Precision includes: repeatability — the variation arising when all efforts are made to keep conditions constant by using the same instrument and operator, and repeating during a short time period; and reproducibility — the variation arising using the same measurement process among different instruments and operators, and over longer time periods. ISO definition (ISO 5725)[edit] According to ISO 57251, Accuracy consists of Trueness (proximity of measurement results to the true value) and Precision (repeatability or reproducibility of the measurement) A shift in the meaning of these terms appeared with the publication of the ISO 5725 series of standards in 1994, which is also reflected in the 2008 issue of the "BIPM International Vocabulary of Metrology" (VIM), items 2.13 and 2.14.[1] According to ISO 57251,[5] the general term "accuracy" is used to describe the closeness of a measurement to the true value. When the term is applied to sets of measurements of the same measurand, it involves a component of random error and a component of systematic error. In this case trueness is the closeness of the mean of a set of measurement results to the actual (true) value and precision is the closeness of agreement among a set of results. ISO 57251 and VIM also avoid the use of the term "bias", previously specified in BS 54971,[6] because it has different connotations outside the fields of science and engineering, as in medicine and law. Accuracy of a target grouping according to BIPM and ISO 5725 Low accuracy, poor precision, good trueness Low accuracy, good precision, poor trueness In binary classification[edit]
Main article: Evaluation of binary classifiers
Accuracy is also used as a statistical measure of how well a binary
classification test correctly identifies or excludes a condition. That
is, the accuracy is the proportion of true results (both true
positives and true negatives) among the total number of cases
examined.[7] To make the context clear by the semantics, it is often
referred to as the "Rand accuracy" or "Rand index".[8][9][10] It is a
parameter of the test.
In psychometrics and psychophysics[edit]
In psychometrics and psychophysics, the term accuracy is
interchangeably used with validity and constant error. Precision is a
synonym for reliability and variable error. The validity of a
measurement instrument or psychological test is established through
experiment or correlation with behavior. Reliability is established
with a variety of statistical techniques, classically through an
internal consistency test like
Cronbach's alpha
This section may be confusing or unclear to readers. Please help us clarify the section. There might be a discussion about this on the talk page. (March 2013) (Learn how and when to remove this template message) The concepts of accuracy and precision have also been studied in the context of databases, information systems and their sociotechnical context. The necessary extension of these two concepts on the basis of theory of science suggests that they (as well as data quality and information quality) should be centered on accuracy defined as the closeness to the true value seen as the degree of agreement of readings or of calculated values of one same conceived entity, measured or calculated by different methods, in the context of maximum possible disagreement.[13] Further information: Precision and recall See also[edit] Accepted and experimental value
Engineering
References[edit] ^ a b c JCGM 200:2008 International vocabulary of metrology — Basic
and general concepts and associated terms (VIM)
^ Taylor, John Robert (1999). An Introduction to Error Analysis: The
Study of Uncertainties in Physical Measurements. University Science
Books. pp. 128–129. ISBN 093570275X.
^ North Atlantic Treaty Organization, Nato Standardization Agency
AAP6  Glossary of terms and definitions, p 43.
^ Creus, Antonio. Instrumentación Industrial[citation needed]
^ BS ISO 57251: "Accuracy (trueness and precision) of measurement
methods and results  Part 1: General principles and definitions.",
p.1 (1994)
^ BS 54971: "Precision of test methods. Guide for the determination
of repeatability and reproducibility for a standard test method."
(1979)
^ Metz, CE (October 1978). "Basic principles of ROC analysis" (PDF).
Semin Nucl Med. 8 (4): 283–98.
^ "Archived copy" (PDF). Archived from the original (PDF) on
20150311. Retrieved 20150809.
^ "What the Fmeasure doesn't measure" (PDF). Arxiv.org. Retrieved 11
December 2017.
^ David M W Powers. "The Problem with Kappa" (PDF).
Anthology.aclweb.org. Retrieved 11 December 2017.
^ Acken, John M. (1997). "none". Encyclopedia of Computer
Science
External links[edit] Look up accuracy, or precision in Wiktionary, the free dictionary. BIPM  Guides in metrology, Guide to the Expression of Uncertainty in
Measurement

Precision is a description of random errors, a measure of statistical variability. Accuracy has two definitions: More commonly, it is a description of systematic errors, a measure of statistical bias; as these cause a difference between a result and a "true" value, ISO calls this trueness. Alternatively, ISO defines accuracy as describing a combination of both types of observational error above (random and systematic), so high accuracy requires both high precision and high trueness. In simplest terms, given a set of data points from repeated measurements of the same quantity, the set can be said to be precise if the values are close to each other, while the set can be said to be accurate if their average is close to the true value of the quantity being measured. The two concepts are independent of each other, so a particular set of data can be said to be either accurate, or precise, or both, or neither. Contents 1 Common definition 1.1 Quantification 2 ISO definition (ISO 5725) 3 In binary classification 4 In psychometrics and psychophysics 5 In logic simulation 6 In information systems 7 See also 8 References 9 External links Common definition[edit] Accuracy is the proximity of measurement results to the true value; precision, the repeatability, or reproducibility of the measurement In the fields of science and engineering, the accuracy of a measurement system is the degree of closeness of measurements of a quantity to that quantity's true value.[1] The precision of a measurement system, related to reproducibility and repeatability, is the degree to which repeated measurements under unchanged conditions show the same results.[1][2] Although the two words precision and accuracy can be synonymous in colloquial use, they are deliberately contrasted in the context of the scientific method. Interestingly, the field of statistics, where the interpretation of measurements plays a central role, prefers to use the terms bias and variability instead of accuracy and precision: bias is the amount of inaccuracy and variability is the amount of imprecision. A measurement system can be accurate but not precise, precise but not accurate, neither, or both. For example, if an experiment contains a systematic error, then increasing the sample size generally increases precision but does not improve accuracy. The result would be a consistent yet inaccurate string of results from the flawed experiment. Eliminating the systematic error improves accuracy but does not change precision. A measurement system is considered valid if it is both accurate and precise. Related terms include bias (nonrandom or directed effects caused by a factor or factors unrelated to the independent variable) and error (random variability). The terminology is also applied to indirect measurements—that is, values obtained by a computational procedure from observed data. In addition to accuracy and precision, measurements may also have a measurement resolution, which is the smallest change in the underlying physical quantity that produces a response in the measurement. In numerical analysis, accuracy is also the nearness of a calculation to the true value; while precision is the resolution of the representation, typically defined by the number of decimal or binary digits. In military terms, accuracy refers primarily to the accuracy of fire (or "justesse de tir"), the precision of fire expressed by the closeness of a grouping of shots at and around the centre of the target.[3] Quantification[edit] See also: False precision In industrial instrumentation, accuracy is the measurement tolerance, or transmission of the instrument and defines the limits of the errors made when the instrument is used in normal operating conditions.[4] Ideally a measurement device is both accurate and precise, with measurements all close to and tightly clustered around the true value. The accuracy and precision of a measurement process is usually established by repeatedly measuring some traceable reference standard. Such standards are defined in the International System of Units (abbreviated SI from French: Système international d'unités) and maintained by national standards organizations such as the National Institute of Standards and Technology in the United States. This also applies when measurements are repeated and averaged. In that case, the term standard error is properly applied: the precision of the average is equal to the known standard deviation of the process divided by the square root of the number of measurements averaged. Further, the central limit theorem shows that the probability distribution of the averaged measurements will be closer to a normal distribution than that of individual measurements. With regard to accuracy we can distinguish: the difference between the mean of the measurements and the reference value, the bias. Establishing and correcting for bias is necessary for calibration. the combined effect of that and precision. A common convention in science and engineering is to express accuracy and/or precision implicitly by means of significant figures. Here, when not explicitly stated, the margin of error is understood to be onehalf the value of the last significant place. For instance, a recording of 843.6 m, or 843.0 m, or 800.0 m would imply a margin of 0.05 m (the last significant place is the tenths place), while a recording of 8436 m would imply a margin of error of 0.5 m (the last significant digits are the units). A reading of 8,000 m, with trailing zeroes and no decimal point, is ambiguous; the trailing zeroes may or may not be intended as significant figures. To avoid this ambiguity, the number could be represented in scientific notation: 8.0 × 103 m indicates that the first zero is significant (hence a margin of 50 m) while 8.000 × 103 m indicates that all three zeroes are significant, giving a margin of 0.5 m. Similarly, it is possible to use a multiple of the basic measurement unit: 8.0 km is equivalent to 8.0 × 103 m. In fact, it indicates a margin of 0.05 km (50 m). However, reliance on this convention can lead to false precision errors when accepting data from sources that do not obey it.[citation needed] Precision includes: repeatability — the variation arising when all efforts are made to keep conditions constant by using the same instrument and operator, and repeating during a short time period; and reproducibility — the variation arising using the same measurement process among different instruments and operators, and over longer time periods. ISO definition (ISO 5725)[edit] According to ISO 57251, Accuracy consists of Trueness (proximity of measurement results to the true value) and Precision (repeatability or reproducibility of the measurement) A shift in the meaning of these terms appeared with the publication of the ISO 5725 series of standards in 1994, which is also reflected in the 2008 issue of the "BIPM International Vocabulary of Metrology" (VIM), items 2.13 and 2.14.[1] According to ISO 57251,[5] the general term "accuracy" is used to describe the closeness of a measurement to the true value. When the term is applied to sets of measurements of the same measurand, it involves a component of random error and a component of systematic error. In this case trueness is the closeness of the mean of a set of measurement results to the actual (true) value and precision is the closeness of agreement among a set of results. ISO 57251 and VIM also avoid the use of the term "bias", previously specified in BS 54971,[6] because it has different connotations outside the fields of science and engineering, as in medicine and law. Accuracy of a target grouping according to BIPM and ISO 5725 Low accuracy, poor precision, good trueness Low accuracy, good precision, poor trueness In binary classification[edit]
Main article: Evaluation of binary classifiers
Accuracy is also used as a statistical measure of how well a binary
classification test correctly identifies or excludes a condition. That
is, the accuracy is the proportion of true results (both true
positives and true negatives) among the total number of cases
examined.[7] To make the context clear by the semantics, it is often
referred to as the "Rand accuracy" or "Rand index".[8][9][10] It is a
parameter of the test.
In psychometrics and psychophysics[edit]
In psychometrics and psychophysics, the term accuracy is
interchangeably used with validity and constant error. Precision is a
synonym for reliability and variable error. The validity of a
measurement instrument or psychological test is established through
experiment or correlation with behavior. Reliability is established
with a variety of statistical techniques, classically through an
internal consistency test like
Cronbach's alpha
This section may be confusing or unclear to readers. Please help us clarify the section. There might be a discussion about this on the talk page. (March 2013) (Learn how and when to remove this template message) The concepts of accuracy and precision have also been studied in the context of databases, information systems and their sociotechnical context. The necessary extension of these two concepts on the basis of theory of science suggests that they (as well as data quality and information quality) should be centered on accuracy defined as the closeness to the true value seen as the degree of agreement of readings or of calculated values of one same conceived entity, measured or calculated by different methods, in the context of maximum possible disagreement.[13] Further information: Precision and recall See also[edit] Accepted and experimental value
Engineering
References[edit] ^ a b c JCGM 200:2008 International vocabulary of metrology — Basic
and general concepts and associated terms (VIM)
^ Taylor, John Robert (1999). An Introduction to Error Analysis: The
Study of Uncertainties in Physical Measurements. University Science
Books. pp. 128–129. ISBN 093570275X.
^ North Atlantic Treaty Organization, Nato Standardization Agency
AAP6  Glossary of terms and definitions, p 43.
^ Creus, Antonio. Instrumentación Industrial[citation needed]
^ BS ISO 57251: "Accuracy (trueness and precision) of measurement
methods and results  Part 1: General principles and definitions.",
p.1 (1994)
^ BS 54971: "Precision of test methods. Guide for the determination
of repeatability and reproducibility for a standard test method."
(1979)
^ Metz, CE (October 1978). "Basic principles of ROC analysis" (PDF).
Semin Nucl Med. 8 (4): 283–98.
^ "Archived copy" (PDF). Archived from the original (PDF) on
20150311. Retrieved 20150809.
^ "What the Fmeasure doesn't measure" (PDF). Arxiv.org. Retrieved 11
December 2017.
^ David M W Powers. "The Problem with Kappa" (PDF).
Anthology.aclweb.org. Retrieved 11 December 2017.
^ Acken, John M. (1997). "none". Encyclopedia of Computer
Science
External links[edit] Look up accuracy, or precision in Wiktionary, the free dictionary. BIPM  Guides in metrology, Guide to the Expression of Uncertainty in
Measurement

Precision is a description of random errors, a measure of statistical variability. Accuracy has two definitions: More commonly, it is a description of systematic errors, a measure of statistical bias; as these cause a difference between a result and a "true" value, ISO calls this trueness. Alternatively, ISO defines accuracy as describing a combination of both types of observational error above (random and systematic), so high accuracy requires both high precision and high trueness. In simplest terms, given a set of data points from repeated measurements of the same quantity, the set can be said to be precise if the values are close to each other, while the set can be said to be accurate if their average is close to the true value of the quantity being measured. The two concepts are independent of each other, so a particular set of data can be said to be either accurate, or precise, or both, or neither. Contents 1 Common definition 1.1 Quantification 2 ISO definition (ISO 5725) 3 In binary classification 4 In psychometrics and psychophysics 5 In logic simulation 6 In information systems 7 See also 8 References 9 External links Common definition[edit] Accuracy is the proximity of measurement results to the true value; precision, the repeatability, or reproducibility of the measurement In the fields of science and engineering, the accuracy of a measurement system is the degree of closeness of measurements of a quantity to that quantity's true value.[1] The precision of a measurement system, related to reproducibility and repeatability, is the degree to which repeated measurements under unchanged conditions show the same results.[1][2] Although the two words precision and accuracy can be synonymous in colloquial use, they are deliberately contrasted in the context of the scientific method. Interestingly, the field of statistics, where the interpretation of measurements plays a central role, prefers to use the terms bias and variability instead of accuracy and precision: bias is the amount of inaccuracy and variability is the amount of imprecision. A measurement system can be accurate but not precise, precise but not accurate, neither, or both. For example, if an experiment contains a systematic error, then increasing the sample size generally increases precision but does not improve accuracy. The result would be a consistent yet inaccurate string of results from the flawed experiment. Eliminating the systematic error improves accuracy but does not change precision. A measurement system is considered valid if it is both accurate and precise. Related terms include bias (nonrandom or directed effects caused by a factor or factors unrelated to the independent variable) and error (random variability). The terminology is also applied to indirect measurements—that is, values obtained by a computational procedure from observed data. In addition to accuracy and precision, measurements may also have a measurement resolution, which is the smallest change in the underlying physical quantity that produces a response in the measurement. In numerical analysis, accuracy is also the nearness of a calculation to the true value; while precision is the resolution of the representation, typically defined by the number of decimal or binary digits. In military terms, accuracy refers primarily to the accuracy of fire (or "justesse de tir"), the precision of fire expressed by the closeness of a grouping of shots at and around the centre of the target.[3] Quantification[edit] See also: False precision In industrial instrumentation, accuracy is the measurement tolerance, or transmission of the instrument and defines the limits of the errors made when the instrument is used in normal operating conditions.[4] Ideally a measurement device is both accurate and precise, with measurements all close to and tightly clustered around the true value. The accuracy and precision of a measurement process is usually established by repeatedly measuring some traceable reference standard. Such standards are defined in the International System of Units (abbreviated SI from French: Système international d'unités) and maintained by national standards organizations such as the National Institute of Standards and Technology in the United States. This also applies when measurements are repeated and averaged. In that case, the term standard error is properly applied: the precision of the average is equal to the known standard deviation of the process divided by the square root of the number of measurements averaged. Further, the central limit theorem shows that the probability distribution of the averaged measurements will be closer to a normal distribution than that of individual measurements. With regard to accuracy we can distinguish: the difference between the mean of the measurements and the reference value, the bias. Establishing and correcting for bias is necessary for calibration. the combined effect of that and precision. A common convention in science and engineering is to express accuracy and/or precision implicitly by means of significant figures. Here, when not explicitly stated, the margin of error is understood to be onehalf the value of the last significant place. For instance, a recording of 843.6 m, or 843.0 m, or 800.0 m would imply a margin of 0.05 m (the last significant place is the tenths place), while a recording of 8436 m would imply a margin of error of 0.5 m (the last significant digits are the units). A reading of 8,000 m, with trailing zeroes and no decimal point, is ambiguous; the trailing zeroes may or may not be intended as significant figures. To avoid this ambiguity, the number could be represented in scientific notation: 8.0 × 103 m indicates that the first zero is significant (hence a margin of 50 m) while 8.000 × 103 m indicates that all three zeroes are significant, giving a margin of 0.5 m. Similarly, it is possible to use a multiple of the basic measurement unit: 8.0 km is equivalent to 8.0 × 103 m. In fact, it indicates a margin of 0.05 km (50 m). However, reliance on this convention can lead to false precision errors when accepting data from sources that do not obey it.[citation needed] Precision includes: repeatability — the variation arising when all efforts are made to keep conditions constant by using the same instrument and operator, and repeating during a short time period; and reproducibility — the variation arising using the same measurement process among different instruments and operators, and over longer time periods. ISO definition (ISO 5725)[edit] According to ISO 57251, Accuracy consists of Trueness (proximity of measurement results to the true value) and Precision (repeatability or reproducibility of the measurement) A shift in the meaning of these terms appeared with the publication of the ISO 5725 series of standards in 1994, which is also reflected in the 2008 issue of the "BIPM International Vocabulary of Metrology" (VIM), items 2.13 and 2.14.[1] According to ISO 57251,[5] the general term "accuracy" is used to describe the closeness of a measurement to the true value. When the term is applied to sets of measurements of the same measurand, it involves a component of random error and a component of systematic error. In this case trueness is the closeness of the mean of a set of measurement results to the actual (true) value and precision is the closeness of agreement among a set of results. ISO 57251 and VIM also avoid the use of the term "bias", previously specified in BS 54971,[6] because it has different connotations outside the fields of science and engineering, as in medicine and law. Accuracy of a target grouping according to BIPM and ISO 5725 Low accuracy, poor precision, good trueness Low accuracy, good precision, poor trueness In binary classification[edit]
Main article: Evaluation of binary classifiers
Accuracy is also used as a statistical measure of how well a binary
classification test correctly identifies or excludes a condition. That
is, the accuracy is the proportion of true results (both true
positives and true negatives) among the total number of cases
examined.[7] To make the context clear by the semantics, it is often
referred to as the "Rand accuracy" or "Rand index".[8][9][10] It is a
parameter of the test.
In psychometrics and psychophysics[edit]
In psychometrics and psychophysics, the term accuracy is
interchangeably used with validity and constant error. Precision is a
synonym for reliability and variable error. The validity of a
measurement instrument or psychological test is established through
experiment or correlation with behavior. Reliability is established
with a variety of statistical techniques, classically through an
internal consistency test like
Cronbach's alpha
This section may be confusing or unclear to readers. Please help us clarify the section. There might be a discussion about this on the talk page. (March 2013) (Learn how and when to remove this template message) The concepts of accuracy and precision have also been studied in the context of databases, information systems and their sociotechnical context. The necessary extension of these two concepts on the basis of theory of science suggests that they (as well as data quality and information quality) should be centered on accuracy defined as the closeness to the true value seen as the degree of agreement of readings or of calculated values of one same conceived entity, measured or calculated by different methods, in the context of maximum possible disagreement.[13] Further information: Precision and recall See also[edit] Accepted and experimental value
Engineering
References[edit] ^ a b c JCGM 200:2008 International vocabulary of metrology — Basic
and general concepts and associated terms (VIM)
^ Taylor, John Robert (1999). An Introduction to Error Analysis: The
Study of Uncertainties in Physical Measurements. University Science
Books. pp. 128–129. ISBN 093570275X.
^ North Atlantic Treaty Organization, Nato Standardization Agency
AAP6  Glossary of terms and definitions, p 43.
^ Creus, Antonio. Instrumentación Industrial[citation needed]
^ BS ISO 57251: "Accuracy (trueness and precision) of measurement
methods and results  Part 1: General principles and definitions.",
p.1 (1994)
^ BS 54971: "Precision of test methods. Guide for the determination
of repeatability and reproducibility for a standard test method."
(1979)
^ Metz, CE (October 1978). "Basic principles of ROC analysis" (PDF).
Semin Nucl Med. 8 (4): 283–98.
^ "Archived copy" (PDF). Archived from the original (PDF) on
20150311. Retrieved 20150809.
^ "What the Fmeasure doesn't measure" (PDF). Arxiv.org. Retrieved 11
December 2017.
^ David M W Powers. "The Problem with Kappa" (PDF).
Anthology.aclweb.org. Retrieved 11 December 2017.
^ Acken, John M. (1997). "none". Encyclopedia of Computer
Science
External links[edit] Look up accuracy, or precision in Wiktionary, the free dictionary. BIPM  Guides in metrology, Guide to the Expression of Uncertainty in
Measurement

Precision is a description of random errors, a measure of statistical variability. Accuracy has two definitions: More commonly, it is a description of systematic errors, a measure of statistical bias; as these cause a difference between a result and a "true" value, ISO calls this trueness. Alternatively, ISO defines accuracy as describing a combination of both types of observational error above (random and systematic), so high accuracy requires both high precision and high trueness. In simplest terms, given a set of data points from repeated measurements of the same quantity, the set can be said to be precise if the values are close to each other, while the set can be said to be accurate if their average is close to the true value of the quantity being measured. The two concepts are independent of each other, so a particular set of data can be said to be either accurate, or precise, or both, or neither. Contents 1 Common definition 1.1 Quantification 2 ISO definition (ISO 5725) 3 In binary classification 4 In psychometrics and psychophysics 5 In logic simulation 6 In information systems 7 See also 8 References 9 External links Common definition[edit] Accuracy is the proximity of measurement results to the true value; precision, the repeatability, or reproducibility of the measurement In the fields of science and engineering, the accuracy of a measurement system is the degree of closeness of measurements of a quantity to that quantity's true value.[1] The precision of a measurement system, related to reproducibility and repeatability, is the degree to which repeated measurements under unchanged conditions show the same results.[1][2] Although the two words precision and accuracy can be synonymous in colloquial use, they are deliberately contrasted in the context of the scientific method. Interestingly, the field of statistics, where the interpretation of measurements plays a central role, prefers to use the terms bias and variability instead of accuracy and precision: bias is the amount of inaccuracy and variability is the amount of imprecision. A measurement system can be accurate but not precise, precise but not accurate, neither, or both. For example, if an experiment contains a systematic error, then increasing the sample size generally increases precision but does not improve accuracy. The result would be a consistent yet inaccurate string of results from the flawed experiment. Eliminating the systematic error improves accuracy but does not change precision. A measurement system is considered valid if it is both accurate and precise. Related terms include bias (nonrandom or directed effects caused by a factor or factors unrelated to the independent variable) and error (random variability). The terminology is also applied to indirect measurements—that is, values obtained by a computational procedure from observed data. In addition to accuracy and precision, measurements may also have a measurement resolution, which is the smallest change in the underlying physical quantity that produces a response in the measurement. In numerical analysis, accuracy is also the nearness of a calculation to the true value; while precision is the resolution of the representation, typically defined by the number of decimal or binary digits. In military terms, accuracy refers primarily to the accuracy of fire (or "justesse de tir"), the precision of fire expressed by the closeness of a grouping of shots at and around the centre of the target.[3] Quantification[edit] See also: False precision In industrial instrumentation, accuracy is the measurement tolerance, or transmission of the instrument and defines the limits of the errors made when the instrument is used in normal operating conditions.[4] Ideally a measurement device is both accurate and precise, with measurements all close to and tightly clustered around the true value. The accuracy and precision of a measurement process is usually established by repeatedly measuring some traceable reference standard. Such standards are defined in the International System of Units (abbreviated SI from French: Système international d'unités) and maintained by national standards organizations such as the National Institute of Standards and Technology in the United States. This also applies when measurements are repeated and averaged. In that case, the term standard error is properly applied: the precision of the average is equal to the known standard deviation of the process divided by the square root of the number of measurements averaged. Further, the central limit theorem shows that the probability distribution of the averaged measurements will be closer to a normal distribution than that of individual measurements. With regard to accuracy we can distinguish: the difference between the mean of the measurements and the reference value, the bias. Establishing and correcting for bias is necessary for calibration. the combined effect of that and precision. A common convention in science and engineering is to express accuracy and/or precision implicitly by means of significant figures. Here, when not explicitly stated, the margin of error is understood to be onehalf the value of the last significant place. For instance, a recording of 843.6 m, or 843.0 m, or 800.0 m would imply a margin of 0.05 m (the last significant place is the tenths place), while a recording of 8436 m would imply a margin of error of 0.5 m (the last significant digits are the units). A reading of 8,000 m, with trailing zeroes and no decimal point, is ambiguous; the trailing zeroes may or may not be intended as significant figures. To avoid this ambiguity, the number could be represented in scientific notation: 8.0 × 103 m indicates that the first zero is significant (hence a margin of 50 m) while 8.000 × 103 m indicates that all three zeroes are significant, giving a margin of 0.5 m. Similarly, it is possible to use a multiple of the basic measurement unit: 8.0 km is equivalent to 8.0 × 103 m. In fact, it indicates a margin of 0.05 km (50 m). However, reliance on this convention can lead to false precision errors when accepting data from sources that do not obey it.[citation needed] Precision includes: repeatability — the variation arising when all efforts are made to keep conditions constant by using the same instrument and operator, and repeating during a short time period; and reproducibility — the variation arising using the same measurement process among different instruments and operators, and over longer time periods. ISO definition (ISO 5725)[edit] According to ISO 57251, Accuracy consists of Trueness (proximity of measurement results to the true value) and Precision (repeatability or reproducibility of the measurement) A shift in the meaning of these terms appeared with the publication of the ISO 5725 series of standards in 1994, which is also reflected in the 2008 issue of the "BIPM International Vocabulary of Metrology" (VIM), items 2.13 and 2.14.[1] According to ISO 57251,[5] the general term "accuracy" is used to describe the closeness of a measurement to the true value. When the term is applied to sets of measurements of the same measurand, it involves a component of random error and a component of systematic error. In this case trueness is the closeness of the mean of a set of measurement results to the actual (true) value and precision is the closeness of agreement among a set of results. ISO 57251 and VIM also avoid the use of the term "bias", previously specified in BS 54971,[6] because it has different connotations outside the fields of science and engineering, as in medicine and law. Accuracy of a target grouping according to BIPM and ISO 5725 Low accuracy, poor precision, good trueness Low accuracy, good precision, poor trueness In binary classification[edit]
Main article: Evaluation of binary classifiers
Accuracy is also used as a statistical measure of how well a binary
classification test correctly identifies or excludes a condition. That
is, the accuracy is the proportion of true results (both true
positives and true negatives) among the total number of cases
examined.[7] To make the context clear by the semantics, it is often
referred to as the "Rand accuracy" or "Rand index".[8][9][10] It is a
parameter of the test.
In psychometrics and psychophysics[edit]
In psychometrics and psychophysics, the term accuracy is
interchangeably used with validity and constant error. Precision is a
synonym for reliability and variable error. The validity of a
measurement instrument or psychological test is established through
experiment or correlation with behavior. Reliability is established
with a variety of statistical techniques, classically through an
internal consistency test like
Cronbach's alpha
This section may be confusing or unclear to readers. Please help us clarify the section. There might be a discussion about this on the talk page. (March 2013) (Learn how and when to remove this template message) The concepts of accuracy and precision have also been studied in the context of databases, information systems and their sociotechnical context. The necessary extension of these two concepts on the basis of theory of science suggests that they (as well as data quality and information quality) should be centered on accuracy defined as the closeness to the true value seen as the degree of agreement of readings or of calculated values of one same conceived entity, measured or calculated by different methods, in the context of maximum possible disagreement.[13] Further information: Precision and recall See also[edit] Accepted and experimental value
Engineering
References[edit] ^ a b c JCGM 200:2008 International vocabulary of metrology — Basic
and general concepts and associated terms (VIM)
^ Taylor, John Robert (1999). An Introduction to Error Analysis: The
Study of Uncertainties in Physical Measurements. University Science
Books. pp. 128–129. ISBN 093570275X.
^ North Atlantic Treaty Organization, Nato Standardization Agency
AAP6  Glossary of terms and definitions, p 43.
^ Creus, Antonio. Instrumentación Industrial[citation needed]
^ BS ISO 57251: "Accuracy (trueness and precision) of measurement
methods and results  Part 1: General principles and definitions.",
p.1 (1994)
^ BS 54971: "Precision of test methods. Guide for the determination
of repeatability and reproducibility for a standard test method."
(1979)
^ Metz, CE (October 1978). "Basic principles of ROC analysis" (PDF).
Semin Nucl Med. 8 (4): 283–98.
^ "Archived copy" (PDF). Archived from the original (PDF) on
20150311. Retrieved 20150809.
^ "What the Fmeasure doesn't measure" (PDF). Arxiv.org. Retrieved 11
December 2017.
^ David M W Powers. "The Problem with Kappa" (PDF).
Anthology.aclweb.org. Retrieved 11 December 2017.
^ Acken, John M. (1997). "none". Encyclopedia of Computer
Science
External links[edit] Look up accuracy, or precision in Wiktionary, the free dictionary. BIPM  Guides in metrology, Guide to the Expression of Uncertainty in
Measurement

Precision is a description of random errors, a measure of statistical variability. Accuracy has two definitions: More commonly, it is a description of systematic errors, a measure of statistical bias; as these cause a difference between a result and a "true" value, ISO calls this trueness. Alternatively, ISO defines accuracy as describing a combination of both types of observational error above (random and systematic), so high accuracy requires both high precision and high trueness. In simplest terms, given a set of data points from repeated measurements of the same quantity, the set can be said to be precise if the values are close to each other, while the set can be said to be accurate if their average is close to the true value of the quantity being measured. The two concepts are independent of each other, so a particular set of data can be said to be either accurate, or precise, or both, or neither. Contents 1 Common definition 1.1 Quantification 2 ISO definition (ISO 5725) 3 In binary classification 4 In psychometrics and psychophysics 5 In logic simulation 6 In information systems 7 See also 8 References 9 External links Common definition[edit] Accuracy is the proximity of measurement results to the true value; precision, the repeatability, or reproducibility of the measurement In the fields of science and engineering, the accuracy of a measurement system is the degree of closeness of measurements of a quantity to that quantity's true value.[1] The precision of a measurement system, related to reproducibility and repeatability, is the degree to which repeated measurements under unchanged conditions show the same results.[1][2] Although the two words precision and accuracy can be synonymous in colloquial use, they are deliberately contrasted in the context of the scientific method. Interestingly, the field of statistics, where the interpretation of measurements plays a central role, prefers to use the terms bias and variability instead of accuracy and precision: bias is the amount of inaccuracy and variability is the amount of imprecision. A measurement system can be accurate but not precise, precise but not accurate, neither, or both. For example, if an experiment contains a systematic error, then increasing the sample size generally increases precision but does not improve accuracy. The result would be a consistent yet inaccurate string of results from the flawed experiment. Eliminating the systematic error improves accuracy but does not change precision. A measurement system is considered valid if it is both accurate and precise. Related terms include bias (nonrandom or directed effects caused by a factor or factors unrelated to the independent variable) and error (random variability). The terminology is also applied to indirect measurements—that is, values obtained by a computational procedure from observed data. In addition to accuracy and precision, measurements may also have a measurement resolution, which is the smallest change in the underlying physical quantity that produces a response in the measurement. In numerical analysis, accuracy is also the nearness of a calculation to the true value; while precision is the resolution of the representation, typically defined by the number of decimal or binary digits. In military terms, accuracy refers primarily to the accuracy of fire (or "justesse de tir"), the precision of fire expressed by the closeness of a grouping of shots at and around the centre of the target.[3] Quantification[edit] See also: False precision In industrial instrumentation, accuracy is the measurement tolerance, or transmission of the instrument and defines the limits of the errors made when the instrument is used in normal operating conditions.[4] Ideally a measurement device is both accurate and precise, with measurements all close to and tightly clustered around the true value. The accuracy and precision of a measurement process is usually established by repeatedly measuring some traceable reference standard. Such standards are defined in the International System of Units (abbreviated SI from French: Système international d'unités) and maintained by national standards organizations such as the National Institute of Standards and Technology in the United States. This also applies when measurements are repeated and averaged. In that case, the term standard error is properly applied: the precision of the average is equal to the known standard deviation of the process divided by the square root of the number of measurements averaged. Further, the central limit theorem shows that the probability distribution of the averaged measurements will be closer to a normal distribution than that of individual measurements. With regard to accuracy we can distinguish: the difference between the mean of the measurements and the reference value, the bias. Establishing and correcting for bias is necessary for calibration. the combined effect of that and precision. A common convention in science and engineering is to express accuracy and/or precision implicitly by means of significant figures. Here, when not explicitly stated, the margin of error is understood to be onehalf the value of the last significant place. For instance, a recording of 843.6 m, or 843.0 m, or 800.0 m would imply a margin of 0.05 m (the last significant place is the tenths place), while a recording of 8436 m would imply a margin of error of 0.5 m (the last significant digits are the units). A reading of 8,000 m, with trailing zeroes and no decimal point, is ambiguous; the trailing zeroes may or may not be intended as significant figures. To avoid this ambiguity, the number could be represented in scientific notation: 8.0 × 103 m indicates that the first zero is significant (hence a margin of 50 m) while 8.000 × 103 m indicates that all three zeroes are significant, giving a margin of 0.5 m. Similarly, it is possible to use a multiple of the basic measurement unit: 8.0 km is equivalent to 8.0 × 103 m. In fact, it indicates a margin of 0.05 km (50 m). However, reliance on this convention can lead to false precision errors when accepting data from sources that do not obey it.[citation needed] Precision includes: repeatability — the variation arising when all efforts are made to keep conditions constant by using the same instrument and operator, and repeating during a short time period; and reproducibility — the variation arising using the same measurement process among different instruments and operators, and over longer time periods. ISO definition (ISO 5725)[edit] According to ISO 57251, Accuracy consists of Trueness (proximity of measurement results to the true value) and Precision (repeatability or reproducibility of the measurement) A shift in the meaning of these terms appeared with the publication of the ISO 5725 series of standards in 1994, which is also reflected in the 2008 issue of the "BIPM International Vocabulary of Metrology" (VIM), items 2.13 and 2.14.[1] According to ISO 57251,[5] the general term "accuracy" is used to describe the closeness of a measurement to the true value. When the term is applied to sets of measurements of the same measurand, it involves a component of random error and a component of systematic error. In this case trueness is the closeness of the mean of a set of measurement results to the actual (true) value and precision is the closeness of agreement among a set of results. ISO 57251 and VIM also avoid the use of the term "bias", previously specified in BS 54971,[6] because it has different connotations outside the fields of science and engineering, as in medicine and law. Accuracy of a target grouping according to BIPM and ISO 5725 Low accuracy, poor precision, good trueness Low accuracy, good precision, poor trueness In binary classification[edit]
Main article: Evaluation of binary classifiers
Accuracy is also used as a statistical measure of how well a binary
classification test correctly identifies or excludes a condition. That
is, the accuracy is the proportion of true results (both true
positives and true negatives) among the total number of cases
examined.[7] To make the context clear by the semantics, it is often
referred to as the "Rand accuracy" or "Rand index".[8][9][10] It is a
parameter of the test.
In psychometrics and psychophysics[edit]
In psychometrics and psychophysics, the term accuracy is
interchangeably used with validity and constant error. Precision is a
synonym for reliability and variable error. The validity of a
measurement instrument or psychological test is established through
experiment or correlation with behavior. Reliability is established
with a variety of statistical techniques, classically through an
internal consistency test like
Cronbach's alpha
This section may be confusing or unclear to readers. Please help us clarify the section. There might be a discussion about this on the talk page. (March 2013) (Learn how and when to remove this template message) The concepts of accuracy and precision have also been studied in the context of databases, information systems and their sociotechnical context. The necessary extension of these two concepts on the basis of theory of science suggests that they (as well as data quality and information quality) should be centered on accuracy defined as the closeness to the true value seen as the degree of agreement of readings or of calculated values of one same conceived entity, measured or calculated by different methods, in the context of maximum possible disagreement.[13] Further information: Precision and recall See also[edit] Accepted and experimental value
Engineering
References[edit] ^ a b c JCGM 200:2008 International vocabulary of metrology — Basic
and general concepts and associated terms (VIM)
^ Taylor, John Robert (1999). An Introduction to Error Analysis: The
Study of Uncertainties in Physical Measurements. University Science
Books. pp. 128–129. ISBN 093570275X.
^ North Atlantic Treaty Organization, Nato Standardization Agency
AAP6  Glossary of terms and definitions, p 43.
^ Creus, Antonio. Instrumentación Industrial[citation needed]
^ BS ISO 57251: "Accuracy (trueness and precision) of measurement
methods and results  Part 1: General principles and definitions.",
p.1 (1994)
^ BS 54971: "Precision of test methods. Guide for the determination
of repeatability and reproducibility for a standard test method."
(1979)
^ Metz, CE (October 1978). "Basic principles of ROC analysis" (PDF).
Semin Nucl Med. 8 (4): 283–98.
^ "Archived copy" (PDF). Archived from the original (PDF) on
20150311. Retrieved 20150809.
^ "What the Fmeasure doesn't measure" (PDF). Arxiv.org. Retrieved 11
December 2017.
^ David M W Powers. "The Problem with Kappa" (PDF).
Anthology.aclweb.org. Retrieved 11 December 2017.
^ Acken, John M. (1997). "none". Encyclopedia of Computer
Science
External links[edit] Look up accuracy, or precision in Wiktionary, the free dictionary. BIPM  Guides in metrology, Guide to the Expression of Uncertainty in
Measurement
