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    Scholarship applications are invited for Wiki Conference Indiabeing held from 18-20 November, 2011 in Mumbai.Apply here.

    Last date for application is August 15, 2011.

    Accuracy and precisionFrom Wikipedia, the free encyclopedia

    "Accuracy" redirects here. For the song by The Cure, seeThree Imaginary Boys.

    In the fields ofscience,engineering,industryandstatistics, the accuracy[1]

    of ameasurementsystem is the degree of closeness of measurements of aquantityto that

    quantity's actual (true)value. The precision[1]

    of a measurement system, also calledreproducibilityorrepeatability, is the degree to which repeated measurements under

    unchanged conditions show the sameresults.[2]

    Although the two words can be

    synonymousincolloquialuse, they are deliberately contrasted in the context of the

    scientific method.

    This glossary serves to introduce the user to the terminology used by LeeCompany engineers in describing out products. These descriptions are

    proposed to serve as a reference point in product discussions to eliminateproblems of definition. While these terms are subjected to differentinterpretation throughout various fields, it is proposed that these definitions beadhered to aid efficient communication.

    AccuracyAccuracy is the degree of error between the intended, specified, or nominalproperty value and actual value. Typically used to define the performanceenvelope of a production lot of parts about the specified nominal. Normallyused to relate single-event performance of multiple parts. Compare toPRECISION.

    Axial MixingSee FLUSHABILITY

    Backlash (Mechanical Hysteresis)Backlash is defined as the amount (usually in microliters) of "play" or error inthe mechanical drive of the pump assembly. This is only noticable when themotor armature changes direction. The error is the result of the clearance

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    between the screw and nut portions of the drive. Properly accounted for withdrive software, the backlash can be made insignificant to accuracy andprecision.

    Carry-over Volume

    See CROSSOVER VOLUME

    Coefficient of Variation (CV)CV is defined as the standard deviation of a distribution of data divided by themean value. This value, expressed in percent, reflects the degree of spread ofdata and is used to define the consistency of the performance or of dispensedvolumes or other parameter.

    Crossover Volume (Dead-leg Volume, Carry-over Volume)Crossover Volume is any internal-geometry-dependent volumetric errorintroduced by the value internal volume between the valving point and the

    common flow point. Most commonly used in discussions of three-way valves, itrefers to the unflushed slug of material between the flowing passage and theclosed port seal.

    Crosstalk (Intra-port Flow)Crosstalk is any response-time-dependent flow or pressure variation betweenany two valves or two ports of a three-way valve. For example, this term refersto the flow that takes place between the Normally Closed and Normally openports of the three-way valve in the time between the beginning of actuation andthe end of actuation, when both ports are partially open.

    Dead-leg VolumeSee CROSSOVER VOLUME

    Flushability (Axial Mixing)Flushability the degree of dispersion or band-broadening introduced by acomponent into a flowing stream. Sometimes referred to as axial mixing, itdefines the stretching of a slug of sample as it passes through a component.Usually discussed in relative or qualitative terms, as the specific definition ofthis characteristic is somewhat complex.

    Response TimeThis term defines the lag time between the input of a control signal and theresulting response of the system or component being monitored. Typical use ofthe response time with a passive component could define the time lag betweena pressure pulse input to a check valve, and the time to close or open the valveseat in response to that pulse. The more common usage is in reference to aactive components, such as solenoid valves. This term then typically definesthe time from the beginning of a normal voltage step-input drive signal, and thepneumatic output from the valve port that is opening or closing as a result of

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    that signal. For further discussion of response times, contact your Lee SalesEngineer.

    Dead VolumeThe actual non-flushable volumes of any component or system flow passages,

    where a dead-end passageway or cavity could retain materials to contaminatesubsequent samples or flow media. This value is highly subjective, as manyfactors come into play to determine the actual dead volume such as miscibility,viscosity, binding energy, etc. The quantity of the former sample still retainedinside the component after flushing with some specified volume is defined asdead volume.

    Intra-port FlowSee CROSSTALK

    Repeatability (Precision)

    The repeatability of any function means consistency of performance even if theperformance is not accurate. Used in reference to valve response times ordispensed volumes. Usually specified in terms of the percent tolerance aboutthe nominal, specified, or mean value. Used to express the total variability of asingle component over multiple events.

    Accuracy indicates proximity of measurement results to the true value, precision to the

    repeatability or reproducibility of the measurement

    A measurement system can be accurate but not precise, precise but not accurate, neither,or both. For example, if anexperimentcontains asystematic error, then increasing the

    sample sizegenerally increases precision but does not improve accuracy. The end resultwould 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 designated validif it is both accurate andprecise. Related

    terms include bias (non-randomor directed effects caused by a factor or factors unrelated

    to theindependent variable) and error(random variability).

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    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 ameasurement

    resolution, which is the smallest change in the underlying physical quantity that produces

    a response in the measurement.

    In the case of full reproducibility, such as when rounding a number to a representable

    floating pointnumber, the wordprecision has a meaning not related to reproducibility.

    For example, in theIEEE 754-2008standard it means the number of bits in the

    significand, so it is used as a measure for the relative accuracy with which an arbitrarynumber can be represented.

    Contents

    [hide]

    1 Accuracy versus precision: the target analogy

    2 Quantifying accuracy and precision

    3 Accuracy and precision in binary classification

    4 Accuracy and precision in psychometrics and psychophysics

    5 Accuracy and precision in logic simulation

    6 Accuracy and precision in information systems

    7 See also

    8 References

    9 External links

    [edit] Accuracy versus precision: the target analogy

    High accuracy, but low precision

    High precision, but low accuracy

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    Accuracy is the degree of veracity while in some contexts precision may mean the degree

    of reproducibility.[citation needed]

    Theanalogyused here to explain the difference between accuracy and precision is the

    target comparison. In this analogy, repeated measurements are compared toarrowsthat

    are shot at a target. Accuracy describes the closeness of arrows to the bullseyeat thetarget center. Arrows that strike closer to the bullseye are considered more accurate. The

    closer a system's measurements to the accepted value, the more accurate the system isconsidered to be.

    To continue the analogy, if a large number of arrows are shot, precision would be the sizeof the arrow cluster. (When only one arrow is shot, precision is the size of the cluster onewouldexpect if this were repeated many times under the same conditions.) When all

    arrows are grouped tightly together, the cluster is considered precise since they all struck

    close to the same spot, even if not necessarily near the bullseye. The measurements areprecise, though not necessarily accurate.

    However, it is notpossible to reliably achieve accuracy in individual measurements

    without precisionif the arrows are not grouped close to one another, they cannot all be

    close to the bullseye. (Their average position might be an accurate estimation of the

    bullseye, but the individual arrows are inaccurate.) See alsocircular error probableforapplication of precision to the science ofballistics.

    [edit] Quantifying accuracy and precision

    See also:False precision

    Ideally a measurement device is both accurate and precise, with measurements all closeto and tightly clustered around the known value. The accuracy and precision of a

    measurement process is usually established by repeatedly measuring sometraceablereferencestandard. Such standards are defined in theInternational System of Unitsand

    maintained by nationalstandards organizationssuch as theNational Institute of Standards

    and Technology.

    This also applies when measurements are repeated and averaged. In that case, the term

    standard erroris 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 ofmeasurements averaged. Further, thecentral limit theoremshows that theprobability

    distributionof the averaged measurements will be closer to a normal distribution thanthat of individual measurements.

    With regard to accuracy we can distinguish:

    the difference between themeanof the measurements and the reference value, the

    bias. Establishing and correcting for bias is necessary forcalibration.

    the combined effect of that and precision.

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    A common convention in science and engineering is to express accuracy and/or precision

    implicitly by means ofsignificant figures. Here, when not explicitly stated, the margin oferror is understood to be one-half 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 8,436 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; thetrailing 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 indicatesthat 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 precisionerrors when accepting data from sources that do not obey it.

    Looking at this in another way, a value of 8 would mean that the measurement has beenmade with a precision of 1 (the measuring instrument was able to measure only down to1s place) whereas a value of 8.0 (though mathematically equal to 8) would mean that the

    value at the first decimal place was measured and was found to be zero. (The measuring

    instrument was able to measure the first decimal place.) The second value is moreprecise. Neither of the measured values may be accurate (the actual value could be 9.5

    but measured inaccurately as 8 in both instances). Thus, accuracy can be said to be the

    'correctness' of a measurement, while precision could be identified as the ability to

    resolve smaller differences.

    Precision is sometimes stratified into:

    Repeatabilitythe 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

    Reproducibilitythe variation arising using the same measurement process

    among different instruments and operators, and over longer time periods.

    [edit] Accuracy and precision in binary classification

    Accuracy is also used as a statistical measure of how well abinary classificationtest

    correctly identifies or excludes a condition.

    Condition as determined by Gold

    standard

    True False

    Test

    outcome

    Positive True positive False positive Positive predictive value

    Negative False negative True negative Negative predictive

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    value

    Sensitivity

    SpecificityAccuracy

    That is, the accuracy is the proportion of true results (bothtrue positivesandtruenegatives) in the population. It is a parameter of the test.

    On the other hand, precision is defined as the proportion of the true positives against all

    the positive results (both true positives andfalse positives)

    An accuracy of 100% means that the measured values are exactly the same as the givenvalues.

    Also seeSensitivity and specificity.

    Accuracy may be determined from Sensitivity and Specificity, providedPrevalenceisknown, using the equation:

    accuracy = (sensitivity)(prevalence) + (specificity)(1 prevalence)

    Theaccuracy paradoxforpredictive analyticsstates that predictive models with a given

    level of accuracy may have greaterpredictive powerthan models with higher accuracy. Itmay be better to avoid the accuracy metric in favor of other metrics such asprecision and

    recall.[citation needed] In situations where the minority class is more important,F-measure

    may be more appropriate, especially in situations with very skewed class imbalance. Analternate performance measure that treats both classes with equal importance is "balanced

    accuracy":

    [edit] Accuracy and precision in psychometrics and

    psychophysics

    Inpsychometricsandpsychophysics, the term accuracy is interchangeably used with

    validityand constant error. Precision is a synonym forreliabilityand variable error. The

    validity of a measurement instrument or psychological test is established throughexperiment or correlation with behavior. Reliability is established with a variety of

    statistical techniques, classically through an internal consistency test likeCronbach's

    http://en.wikipedia.org/wiki/Sensitivity_%28tests%29http://en.wikipedia.org/wiki/Sensitivity_%28tests%29http://en.wikipedia.org/wiki/Specificity_%28tests%29http://en.wikipedia.org/wiki/Specificity_%28tests%29http://en.wikipedia.org/wiki/True_positivehttp://en.wikipedia.org/wiki/True_positivehttp://en.wikipedia.org/wiki/True_positivehttp://en.wikipedia.org/wiki/True_negativehttp://en.wikipedia.org/wiki/True_negativehttp://en.wikipedia.org/wiki/True_negativehttp://en.wikipedia.org/wiki/True_negativehttp://en.wikipedia.org/wiki/False_positivehttp://en.wikipedia.org/wiki/False_positivehttp://en.wikipedia.org/wiki/False_positivehttp://en.wikipedia.org/wiki/Sensitivity_and_specificityhttp://en.wikipedia.org/wiki/Sensitivity_and_specificityhttp://en.wikipedia.org/wiki/Sensitivity_and_specificityhttp://en.wikipedia.org/wiki/Prevalencehttp://en.wikipedia.org/wiki/Prevalencehttp://en.wikipedia.org/wiki/Prevalencehttp://en.wikipedia.org/wiki/Accuracy_paradoxhttp://en.wikipedia.org/wiki/Accuracy_paradoxhttp://en.wikipedia.org/wiki/Accuracy_paradoxhttp://en.wikipedia.org/wiki/Predictive_analyticshttp://en.wikipedia.org/wiki/Predictive_analyticshttp://en.wikipedia.org/wiki/Predictive_analyticshttp://en.wikipedia.org/wiki/Predictive_powerhttp://en.wikipedia.org/wiki/Predictive_powerhttp://en.wikipedia.org/wiki/Predictive_powerhttp://en.wikipedia.org/wiki/Precision_and_recallhttp://en.wikipedia.org/wiki/Precision_and_recallhttp://en.wikipedia.org/wiki/Precision_and_recallhttp://en.wikipedia.org/wiki/Precision_and_recallhttp://en.wikipedia.org/wiki/Wikipedia:Citation_neededhttp://en.wikipedia.org/wiki/Wikipedia:Citation_neededhttp://en.wikipedia.org/wiki/Wikipedia:Citation_neededhttp://en.wikipedia.org/wiki/F-measurehttp://en.wikipedia.org/wiki/F-measurehttp://en.wikipedia.org/wiki/F-measurehttp://en.wikipedia.org/w/index.php?title=Accuracy_and_precision&action=edit&section=4http://en.wikipedia.org/w/index.php?title=Accuracy_and_precision&action=edit&section=4http://en.wikipedia.org/wiki/Psychometricshttp://en.wikipedia.org/wiki/Psychometricshttp://en.wikipedia.org/wiki/Psychometricshttp://en.wikipedia.org/wiki/Psychophysicshttp://en.wikipedia.org/wiki/Psychophysicshttp://en.wikipedia.org/wiki/Psychophysicshttp://en.wikipedia.org/wiki/Validity_%28statistics%29http://en.wikipedia.org/wiki/Validity_%28statistics%29http://en.wikipedia.org/wiki/Reliability_%28statistics%29http://en.wikipedia.org/wiki/Reliability_%28statistics%29http://en.wikipedia.org/wiki/Reliability_%28statistics%29http://en.wikipedia.org/wiki/Cronbach%27s_alphahttp://en.wikipedia.org/wiki/Cronbach%27s_alphahttp://en.wikipedia.org/wiki/Cronbach%27s_alphahttp://en.wikipedia.org/wiki/Reliability_%28statistics%29http://en.wikipedia.org/wiki/Validity_%28statistics%29http://en.wikipedia.org/wiki/Psychophysicshttp://en.wikipedia.org/wiki/Psychometricshttp://en.wikipedia.org/w/index.php?title=Accuracy_and_precision&action=edit&section=4http://en.wikipedia.org/wiki/F-measurehttp://en.wikipedia.org/wiki/Wikipedia:Citation_neededhttp://en.wikipedia.org/wiki/Precision_and_recallhttp://en.wikipedia.org/wiki/Precision_and_recallhttp://en.wikipedia.org/wiki/Predictive_powerhttp://en.wikipedia.org/wiki/Predictive_analyticshttp://en.wikipedia.org/wiki/Accuracy_paradoxhttp://en.wikipedia.org/wiki/Prevalencehttp://en.wikipedia.org/wiki/Sensitivity_and_specificityhttp://en.wikipedia.org/wiki/False_positivehttp://en.wikipedia.org/wiki/True_negativehttp://en.wikipedia.org/wiki/True_negativehttp://en.wikipedia.org/wiki/True_positivehttp://en.wikipedia.org/wiki/Specificity_%28tests%29http://en.wikipedia.org/wiki/Sensitivity_%28tests%29
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    alphato ensure sets of related questions have related responses, and then comparison of

    those related question between reference and target population.[citation needed]

    [edit] Accuracy and precision in logic simulation

    Inlogic simulation, a common mistake in evaluation of accurate models is to compare alogic simulation modelto atransistorcircuit simulation model. This is a comparison of

    differences in precision, not accuracy. Precision is measured with respect to detail andaccuracy is measured with respect to reality.[3][4]

    [edit] Accuracy and precision in information systems

    The concepts of accuracy and precision have also been studied in the context of data

    bases, 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 asdata

    qualityandinformation quality) should be centered on accuracy defined as the closenessto 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.[5]

    [edit] See also

    Accuracy class

    ANOVA Gauge R&R

    ASTME177 Standard Practice for Use of the Terms Precision and Bias in ASTM

    Test Methods

    Experimental uncertainty analysis Failure assessment

    Gain (information retrieval)

    Precision bias

    Precision engineering

    Precision (statistics)

    Accepted and experimental value

    [edit] References

    1. ^

    a

    b

    JCGM 200:2008 International vocabulary of metrology

    Basic and generalconcepts and associated terms (VIM)

    2. ^John Robert Taylor (1999).An Introduction to Error Analysis: The Study ofUncertainties in Physical Measurements. University Science Books. pp. 128129.ISBN0-935702-75-X.

    3. ^John M. Acken, Encyclopedia of Computer Science and Technology, Vol 36,1997, page 281-306

    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ction=edit&section=8http://en.wikipedia.org/wiki/Accepted_and_experimental_valuehttp://en.wikipedia.org/wiki/Precision_%28statistics%29http://en.wikipedia.org/wiki/Precision_engineeringhttp://en.wikipedia.org/wiki/Precision_biashttp://en.wikipedia.org/wiki/Gain_%28information_retrieval%29http://en.wikipedia.org/wiki/Failure_assessmenthttp://en.wikipedia.org/wiki/Experimental_uncertainty_analysishttp://en.wikipedia.org/wiki/ASTMhttp://en.wikipedia.org/wiki/ANOVA_Gauge_R%26Rhttp://en.wikipedia.org/wiki/Accuracy_classhttp://en.wikipedia.org/w/index.php?title=Accuracy_and_precision&action=edit&section=7http://en.wikipedia.org/wiki/Accuracy_and_precision#cite_note-4http://en.wikipedia.org/wiki/Information_qualityhttp://en.wikipedia.org/wiki/Data_qualityhttp://en.wikipedia.org/wiki/Data_qualityhttp://en.wikipedia.org/w/index.php?title=Accuracy_and_precision&action=edit&section=6http://en.wikipedia.org/wiki/Accuracy_and_precision#cite_note-2http://en.wikipedia.org/wiki/Accuracy_and_precision#cite_note-2http://en.wikipedia.org/wiki/Transistor_modelshttp://en.wikipedia.org/wiki/Transistorhttp://en.wikipedia.org/wiki/Electronic_circuit_simulationhttp://en.wikipedia.org/wiki/Logic_simulationhttp://en.wikipedia.org/w/index.php?title=Accuracy_and_precision&action=edit&section=5http://en.wikipedia.org/wiki/Wikipedia:Citation_neededhttp://en.wikipedia.org/wiki/Cronbach%27s_alpha
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    4. ^1990 Workshop on Logic-Level Modelling for ASICS, Mark Glasser, RobMathews, and John M. Acken, SIGDA Newsletter, Vol 20. Number 1, June 1990

    5. ^Ivanov, K.(1972)."Quality-control of information: On the concept of accuracyof information in data banks and in management information systems". The

    University of Stockholm and The Royal Institute of Technology. Doctoral

    dissertation. Further details are found inIvanov, K.(1995). A subsystem in thedesign of informatics: Recalling an archetypal engineer. In B.. Dahlbom (Ed.),The infological equation: Essays in honor of Brje Langefors , (pp. 287-301).

    Gothenburg: Gothenburg University, Dept. of Informatics (ISSN 1101-7422).

    [edit] External links

    Look upaccuracy, orprecisioninWiktionary, the free dictionary.

    BIPM - Guides in metrology- Guide to the Expression of Uncertainty inMeasurement (GUM) and International Vocabulary of Metrology (VIM)

    "Beyond NIST Traceability: What really creates accuracy"- ControlledEnvironments magazine

    Precision and Accuracy with Three Psychophysical Methods

    Guidelines for Evaluating and Expressing the Uncertainty of NIST Measurement

    Results, Appendix D.1: Terminology

    Accuracy and Precision

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    B. Accuracy vs. Precision, and Error vs. Uncertainty

    When we discuss measurements or the results of measuring instruments there are severaldistinct concepts involved which are often confused with one another. This sectionsdescribes four important ideas and establishes the differences between them. The first

    distinction is between Accuracy and Precision.

    Accuracy

    Accuracy refers to the agreement between a measurement and the true or correct value. Ifa clock strikes twelve when the sun is exactly overhead, the clock is said to be accurate.

    The measurement of the clock (twelve) and the phenomena it is meant to measure (The

    sun located at zenith) are in agreement. Accuracy cannot be discussed meaningfullyunless the true value is known or is knowable. (Note: The true value of a measurement

    can never be known.Read more about this.)

    Accuracy refers to the agreementof the measurement and the true value and does nottell

    you about the quality of the instrument. The instrument may be of high quality and still

    disagree with the true value. In the example above it was assumed that the purpose of the

    clock is to measure the location of the sun as it appears to move accross the sky.However, in our system of time zones the sun is directly overhead at twelve O'clock only

    if you are at the center of the time zone. If you are at the eastern edge of the time zone the

    sun is directly overhead around 11:30, while at the western edge the sun is directlyoverhead at around 12:30. So at either edge the twelve O'clock reading does not agree

    with the phenomena of the sun being at the local zenith and we might complain that the

    clock is not accurate. Here the accuracy of the clock reading is affected by our system oftime zones rather than by any defect of the clock.

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    In the case of time zones however clocks measure something slightly more abstract than

    the location of the sun. We define the clock at the center of the time zone to be correct ifit matches the sun, we then define all the other clocks in that time zone to be correct if

    they match the central clock. Thus a clock at the Eastern edge of a time zone that reads

    11:30 when the sun is overhead would still be accurate since it agrees with the central

    clock. A clock that read 12:00 would not be accurate at that time. The idea to get used tohere is that accuracy only refers to the agreement between the measured value and the

    expected value and that this may or may not say something about the quality of the

    measuring instrument. A stoppedclock is accurate at least once each day.

    Precision

    Precision refers to the repeatability of measurement. It does not require us to know the

    correct or true value. If each day for several years a clock reads exactly 10:17 AM when

    the sun is at the zenith, this clock is very precise. Since there are more than thirty millionseconds in a year this device is moreprecise than one part in one million! That is a very

    fine clock indeed! You should take note here that we do not need to consider thecomplications of edges of time zones to decide that this is a good clock. The truemeaning of noon is not important because we only care that the clock is giving a

    repeatable result.

    Error

    Error refers to the disagreement between a measurement and the true or accepted value.

    You may be amazed to discover that error is not that important in the discussion of

    experimental results. This statement certainly needs some explanation.

    As with accuracy, you must know the true or correct value to discuss your error. Butconsider what science is about. The central objective is to discover new things. If they are

    new, then we do not know what the true value is ahead of time. Thus it is not possible todiscuss our error. You might raise the possibility that the experiment has a defective

    component or incorrect assumption so that an error is made. Of course the scientist is

    concerned about this. Typically there has been much discussion with other scientists anda review of the methods to try to avoid exactly this possibility. However, if an error

    occurs we simply will not know it. The true value has not yet been established and there

    is no other guide. The good scientist assumes the experiment is not in error. It is the onlychoice available. Later research, attempts by other scientists to repeat the result, will

    hopefully reveal any problems, but the first time around there is no such guide.

    Students in science classes are in an artificial situation. Their experiments are necessarilyrepetitions of previous work, so the results are known. Because of this students learn a

    poor lesson about science. Students often are very conscious of error to the point where

    they assume it happens in every experiment. This is distracting to the project of becominga scientist. If you want to benefit most from your laboratory experiences, you will need to

    do some judicious pretending. After the experiment has been conducted, while you write

    up the result in your lab report, assume that error is not a consideration. Your team has

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    done the best it can have done in the lab and you must account for the results on that

    basis. Do not write "human error" as any part of your lab report. It is in the first placeembarrassing, and in our experience as faculty members, it is rarely the source of

    experimental problems. (Well over half of problems producing bad laboratory results are

    due to analysis errors in the report! Look here first.)

    Uncertainty

    Uncertainty of a measured value is an interval around that value such that any repetition

    of the measurement will produce a new result that lies within this interval. This

    uncertainty interval is assigned by the experimenter following established principles ofuncertainty estimation. One of the goals of this document is to help you become

    proficient at assigning and working with uncertainty intervals.

    Uncertainty, rather than error, is the important term to the working scientist. In a sort of

    miraculous way uncertainty allows the scientist to make completely certain statements.

    Here is an example to see how this works.

    Let us say that your classmate has measured the width of a standard piece of notebook

    paper and states the result as 8.53 0.08 inches. By stating the uncertainty to be 0.08inches your classmate is claiming with confidence that every reasonable measurement of

    this piece of paper by other experimenters will produce a value not less than 8.45 inchesand not greater than 8.61 inches.

    Suppose you measured the length of your desk, with a ruler or tape measure, and the

    result was one meter and twenty centimeters (L = 1.20 m). Now the true length is notknown here, in part because you do not have complete knowledge of the manufacture of

    the measuring device, and because you cannot see microscopically to confirm that theedge of the table exactly matches the marks on the device. Thus you cannot discuss error

    in this case. Nevertheless you would not say with absolute certainty that L = 1.20 m.

    However it is quite easy to imagine that you could be certain that the desk was not morethan ten centimeters (~ five inches) different than your measurement. You may have

    experience with tape measures. And based on that experience, you are sure that your tape

    measure could not be stretched out by five inches compared to its proper length. If you do

    not have this confidence, perhaps ten inches or a foot would make you confident. Aftermeasuring you might say "This desk is not longer than 1.35 m and not shorter than 0.95

    m." You could make this statement with complete confidence. The scientist would write

    L = 1.20 0.15 m. The format is "value plus or minus uncertainty."

    Notice that it is always possible to construct a completely certain sentence. In the worst

    case we might say the desk is not shorter than zero meters and not longer than four

    meters (because it would not fit the room). This measurement may be nearly useless, butit is completely certain! By stating a confidence interval for a measurement the scientist

    makes statements that any reasonable scientist must agree with. The skill comes in

    getting the confidence intervals (the uncertainty) to be as small as possible.

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    This is your task in the laboratory. Every measurement you make should be considered

    along with a confidence interval. You should then assign this uncertainty to themeasurement at the time that you record the data.

    Uncertainty: Having presented the example, here is the definition of uncertainty.

    The uncertainty in a stated measurement is the interval of confidence around themeasured value such that the measured value is certain not to lie outside this

    stated interval.

    Uncertainties may also be stated along with a probability. In this case the

    measured value has the stated probability to lie within the confidence interval. A

    particularly common example is one standard deviation (SD) for the average of a

    random sample. The format "value 1 SD" means that if you repeat themeasurement, 68% of the time your new measurement will fall in this interval.

    True values vs. Accepted values

    Check your understanding of these terms by working through the example below.

    A metal rod about 4 inches long has been passed around to several groups of

    students. Each group is asked to measure the length of the rod. Each group has

    five students and each student independently measures the rod and records

    his or her result.

    StudentGroup

    Student 1 Student 2 Student 3 Student 4 Student 5

    Group A 10.1 10.4 9.6 9.9 10.8

    Group B 10.135 10.227 10.201 10.011 10.155

    Group C 12.14 12.17 12.15 12.14 12.18

    Group D 10.05 10.82 8.01 11.5 10.77

    Group E 10 11 10 10 10

    A

    B

    Which group has the most

    accurate measurement? A

    B

    Which group has the most precise

    measurement?

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    C

    D

    E

    C

    D

    E

    A

    B

    C

    D

    E

    Which group has the greatest

    error? A

    B

    C

    D

    E

    Which group has the greatest

    uncertainty?

    We now recieve a report from the machine shop where the rod was

    manufactured. This very reputable firm certifies the rod to be 4 inches long to

    the nearest thousandths of an inch. Answer the questions below given this

    new information. Note that the questions are slightly different.(4.000 inches = 10.160 cm)

    A

    B

    C

    D

    E

    Which group has the least

    accurate measurement? A

    B

    C

    D

    E

    Which group has the least precise

    measurement?

    A

    B

    C

    Which group has the smallest

    error? A

    B

    C

    Which group has the smallest

    uncertainty?

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    D

    E

    D

    E

    The accuracy is the degree of closeness of the measured value to its "true" value. Thisvalue is generally diffined as a purcentage of the capacity of the sensor or instrument in

    the unit of measurement. For example, on our Centor Easy force gauge withinternal

    sensor, the accuracy is 0.1% FS. It means that if you have a sensor with a capacity of100lb, the accuracy of the complete gauge is 0.1% of 100lb = 0.1lb.

    You can find this value with different spelling: 0.1%, 0.1% of the full scale, 0.1% FS

    (FS: Full scale), or 0.1lb

    Repeatability or test-retest reliability[1]

    is thevariationinmeasurementstaken by a

    single person orinstrumenton the same item and under the same conditions. Ameasurement may be said to be repeatable when this variation is smaller than some

    agreed limit. According to the Guidelines for Evaluating and Expressing the Uncertainty

    of NIST Measurement Results, repeatability conditions include:

    the same measurement procedure

    the same observer

    the same measuring instrument, used under the same conditions

    the same location

    repetition over a short period of time.

    Repeatability methods were developed by Bland and Altman (1986).[2]

    The repeatability

    coefficient is a precision measure which represents the value below which theabsolutedifferencebetween two repeated test results may be expected to lie with a probability of

    95%. Thestandard deviationunder repeatability conditions is part ofprecisionand

    accuracy.

    accuracy The difference between a measurement reading and the true value of that

    measurement.amplification The movement of a measuring instrument's contact points

    in relation to the amount of readout on the needle or scale.bias The predicted

    difference on average between the measurement and the true value. Bias is also known as

    accuracy.calibration The comparison of a device with unknown accuracy to a devicewith a known, accurate standard to eliminate any variation in the device being checked.

    caliper A measuring instrument with two pairs of jaws on one end and a long beamcontaining a marked scale of unit divisions. One pair of jaws measures external features;

    the other pair measures internal features.coordinate measuring machine A

    sophisticated measuring instrument with a flat polished table and a suspended probe thatmeasures parts in three-dimensional space.correction factor The amount of deviation

    in a measurement that is accounted for in the calibration process. You can either add the

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    correction factor to the measured value or adjust the measuring instrument.depth gage

    A type of measuring instrument that measures the depth of holes, slots, or recesses. dialindicator A measuring instrument with a contact point attached to a spindle and gears

    that moves a pointer on the dial. Dial indicators have graduations that are available for

    reading different measurement values.discrimination The distance between two lines

    on a scale or the fineness of an instrument's divisions of measurement units. drift Theactual change in the measurement value when the same characteristic is measured under

    the same conditions, same operator, at different points in time. Drift indicates how often a

    measurement needs recalibration.error The amount of deviation from a standard orspecification. Errors should be eliminated in the measuring process.error of measurement

    The actual difference between a measurement value and the known standard value.

    gage A device that determines whether or not a part feature is within specified limits.Most gages do not provide an actual measurement value. However, measuring

    instruments are also sometimes called gages.granite A dense, wear-resistant material

    that is capable of excellent flatness. Granite is often used for inspection surfaces.graph

    A diagram that represents the variation of one variable compared to another. height gage

    A type of measuring instrument with a precision finished base, a beam that is at a rightangle to the base, and an indicator.hysteresis The delay between the action and

    reaction of a measuring instrument. Hysteresis is the amount of error that results whenthis action occurs.linearity The amount of error change throughout an instrument's

    measurement range. Linearity is also the amount of deviation from an instrument's ideal

    straight-line performance.measuring instrument A device used to inspect, measure,test, or examine parts in order to determine compliance with required specifications.

    micrometer A U-shaped measuring instrument with a threaded spindle that slowly

    advances toward a small anvil. Micrometers are available in numerous types for

    measuring assorted dimensions and features.plug gage A hardened, cylindrical gageused to inspect the size of a hole. Plug gages are available in standardized diameters.

    precision The degree to which an instrument will repeat the same measurement over a

    period of time.repeatability The ability to obtain consistent results when measuring the

    same part with the same measuring instrument.resolution The smallest change in ameasured value that the instrument can detect. Resolution is also known as sensitivity.

    rule of ten The inspection guideline stating that a measuring instrument must be ten

    times more precise than the acceptable tolerance of the inspected part feature.slopeThe angle of a line that appears when comparing two variables on a graph.specified

    range of measurement The limit of measurement values that an instrument is capable

    of reading. The dimension being measured must fit inside this range.stability Theability of a measuring instrument to retain its calibration over a long period of time.

    Stability determines an instrument's consistency over time.standard A recognized true

    value. Calibration must compare measurement values to a known standard.systematic

    error An error that is not determined by chance but is introduced by an inaccuracy inthe system. Systematic errors are predictable and expected.thermal characteristic The

    way a material behaves due to changes in heat. Measuring instruments have thermally

    stable characteristics so that they are not affected by temperature increases.toleranceThe unwanted but acceptable deviation from a desired dimension.variation A

    difference between two or more similar things.

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    Equally important to the dollar budget is the error budget, which is often overlooked or

    determined de facto by cost constraints. For optimum system performance, eachindividual system element needs an acceptable error allocation. In determining system

    error budgets, "repeatability" is often confused with "reproducibility".

    The accepted definition of "repeatability" is the closeness of agreement among a numberof consecutive measurements of outputs for the same input where this input is

    approached from the same direction after a transversal of input across the full-scale span.

    The accepted definition of "reproducibility" is the closeness of agreement among a

    number of repeated measurements of outputs for the same input where this input is

    approached from any direction and these measurements are made over a period of time.

    The subtle difference between "repeatability" and "reproducibility" is as follows;

    (a) Repeatability includes neither drift errors (since consecutive measurements over a

    period of time are too short for drift to be afactor) nor hysteresis,

    (b) Reproducibility includes drift (repeated measurements over any length of time),

    hysteresis, and repeatability. Note reproducibility includes repeatability.

    All measurements are made within the test units allowed range and operating conditions.

    Extensive Definition

    Reproducibility is one of the main principles of thescientific method, and refers to the

    ability of a test orexperimentto be accurately reproduced, or replicated, by someone elseworking independently.

    Reproducibility is different fromrepeatability, which measures the success rate in

    successive experiments, possibly conducted by the same experimenters. Reproducibility

    relates to the agreement of test results with different operators, test apparatus, andlaboratory locations. It is often reported as astandard deviation.

    While repeatability of scientific experiments is desirable, it is not considered necessary to

    establish the scientific validity of a theory. For example, thecloningof animals isdifficult to repeat, but has been reproduced by various teams working independently, and

    is a well established research domain. One failed cloning does not mean that the theory is

    wrong or unscientific. Repeatability is often low inprotosciences.

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    The results of an experiment performed by a particularresearcher or group of researchers

    are generally evaluated by other independent researchers by reproducing the originalexperiment. They repeat the same experiment themselves,