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INTRODUCTION TO METROLOGY

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Title: INTRODUCTION TO METROLOGY


1
INTRODUCTION TO METROLOGY
2
Definitions
  • Metrology is the study of measurements
  • Measurements are quantitative observations
    numerical descriptions

3
Overview
  • This longer lecture explores general principles
    of metrology
  • Next 3 shorter lectures apply principles to
    specific measurements weight, volume, pH
  • Later will talk about measuring light
    transmittance (spectrophotometry)

4
We Want ToMake Good Measurements
  • Making measurements is woven throughout daily
    life in a lab.
  • Often take measurements for granted, but
    measurements must be good.
  • What is a good measurement?

5
Example
  • A man weighs himself in the morning on his
    bathroom scale, 172 pounds.
  • Later, he weighs himself at the gym,173 pounds.

6
Questions
  • How much does he really weigh?

7
  • Do you trust one or other scale? Which one?
    Could both be wrong? Do you think he actually
    gained a pound?

8
  • Are these good measurements?

9
Not Sure
  • We are not exactly certain of the mans true
    weight because
  • Maybe his weight really did change always
    sample issues
  • Maybe one or both scales are wrong always
    instrument issues

10
Do We Really Care?
  • Do you care if he really gained a pound?
  • How many think give or take a pound is OK?

11
Another Example
  • Suppose a premature baby is weighed. The weight
    is recorded as 5 pounds 3 ounces and the baby is
    sent home.
  • Do we care if the scale is off by a pound?

12
GoodMeasurements
  • A good measurement is one that can be trusted
    when making decisions.
  • We just made judgments about scales.
  • We make this type of judgment routinely.

13
In The Lab
  • Anyone who works in a lab makes judgments about
    whether measurements are good enough
  • But often the judgments are made subconsciously
  • Differently by different people
  • Want to make decisions
  • Conscious
  • Consistent

14
Quality Systems
  • All laboratory quality systems are concerned with
    measurements
  • All want good measurements that can be
    trusted
  • Measurements should be made consciously and
    consistently

15
Need
  • Awareness of issues so can make good
    measurements.
  • Language to discuss measurements.
  • Tools to evaluate measurements.

16
MetrologyVocabulary
  • Very precise science with imprecise vocabulary
  • (word precise has several precise meanings that
    are, without uncertainty, different)
  • Words have multiple meanings, but specific
    meanings

17
Vocabulary
  • Units of measurement
  • Standards
  • Calibration
  • Traceability
  • Tolerance
  • Accuracy
  • Precision
  • Errors
  • Uncertainty

18
Units OfMeasurement
  • Units define measurements
  • Example, gram is the unit for mass
  • What is the mass of a gram? How do we know?

19
Definitions MadeBy Agreement
  • Definitions of units are made by international
    agreements, SI system
  • Example, kilogram prototype in France
  • Ultimate definition of a kg
  • K10 and K20 are standards at NIST that are
    compared regularly to the prototype in France

20
External Authority
  • Measurements are always made in accordance with
    external authority
  • Early authority for length was Pharaohs arm
    length

21
  • A standard is an external authority
  • Also, standard is a physical embodiment of a unit

22
Standards Are
  • Physical objects, the properties of which are
    known with sufficient accuracy to be used to
    evaluate other items.

23
Standards AreAffected By The Environment
  • Units are unaffected by the environment, but
    standards are
  • Example, Pharaohs arm length might change
  • Example, a ruler is a physical embodiment of
    centimeters
  • Can change with temperature
  • But the unit cm doesnt change

24
StandardsAlso Are
  • In chemical and biological assays, substances or
    solutions used to establish the response of an
    instrument or assay method to an analyst
  • See these in spectrophotometry labs

25
StandardsAlso Are
  • Documents established by consensus and approved
    by a recognized body that establish rules to make
    a process consistent
  • Example ISO 9000 is a Standard
  • ASTM standard method for calibrating a
    micropipettor is the recommended procedure

26
Calibration Is
  • Bringing a measuring system into accordance with
    external authority, using standards
  • For example, calibrating a balance
  • Use standards that have known masses
  • Relate response of your balance to units of kg
  • Will do this in lab

27
PerformanceVerification Is
  • Check of the performance of an instrument or
    method without adjusting it.

28
Tolerance Is
  • Amount of error that is allowed in the
    calibration of a particular item. National and
    international standards specify tolerances.

29
Example
  • Standards for balance calibration can have slight
    variation from true value
  • Highest quality 100 g standards have a tolerance
    of 2.5 mg
  • 99.99975-100.00025 g
  • Leads to uncertainty in all weight measurements

30
Traceability Is
  • The chain of calibrations, genealogy, that
    establishes the value of a standard or
    measurement
  • In the U.S. traceability for most physical and
    some chemical standards goes back to NIST

31
From Basic Laboratory Methods for Biotechnology
Textbook and Laboratory Reference, Seidman and
Moore, 2000
32
Traceability
  • Note in this catalog example, traceable to NIST

33
Vocabulary
  • Standards
  • Calibration
  • Traceability
  • Tolerance
  • Play with these ideas in labs

34
Accuracy AndPrecision Are
  • Accuracy is how close an individual value is to
    the true or accepted value
  • Precision is the consistency of a series of
    measurements

From Basic Laboratory Methods for Biotechnology
Textbook and Laboratory Reference, Seidman and
Moore, 2000
35
Express Accuracy
  • error True value measured value X 100
  • True value
  • Will calculate this in volume lab

36
Express Precision
  • Standard deviation (p. 187-190)
  • Expression of variability
  • Take the mean (average)
  • Calculate how much each measurement deviates from
    mean
  • Take an average of the deviation, so it is the
    average deviation from the mean
  • Try this in the volume lab

37
Error Is
  • Error is responsible for the difference between a
    measured value and the true value

38
CategoriesOf Errors
  • Three types of error
  • Gross
  • Random
  • Systematic

39
Gross Error
  • Blunders

40
Random Error
  • In U.S., weigh particular 10 g standard every
    day. They see
  • 9.999590 g, 9.999601 g, 9.999592 g .
  • What do you think about this?

41
Random Error
  • Variability
  • No one knows why
  • They correct for humidity, barometric pressure,
    temperature
  • Error that cannot be eliminated. Called random
    error

42
Random Error
  • Do you think that repeating the measurement over
    and over would allow us to be more certain of the
    true weight of this standard?

43
Random Error
  • Yes, because in the presence of only random
    error, the mean is more likely to be correct if
    repeat the measurement many times
  • Standard in this example is probably really a bit
    light
  • Average of all the values is a good estimate of
    its true weight

44
Random ErrorAnd Accuracy
  • In presence of only random error, average value
    will tend to be correct
  • With only one or a few measurements, may or may
    not be accurate see picture b in next slide

45
From Basic Laboratory Methods for Biotechnology
Textbook and Laboratory Reference, Seidman and
Moore, 2000
46
MeasurementVariability
Measurement value
FIRST MEASUREMENT OF SAME THING
47
MeasurementVariability
Measurement value
THREE MEASUREMENTS OF THE SAME THING
48
MeasurementVariability
Measurement value
SEVEN MEASUREMENTS OF THE SAME THING
49
MeasurementVariability
Measurement value
MORE MEASUREMENTS OF THE SAME THING
50
MeasurementVariability
Mean Median Mode
Repeated measurements of the same thing tend to
be Normally distributed
51
There Is AlwaysRandom Error
  • If cant see it, system isnt sensitive enough
  • Less sensitive balance might read
  • 10.00 g, 10.00 g, 10.00 g
  • Versus 9.999590 g, 9.999601 g, 9.999592 g .
  • See the variability with the sensitive balance

52
So
  • Can we ever be positive of true weight of that
    standard?
  • No
  • There is uncertainty in every weight measurement

53
RelationshipRandom Error And Precision
  • Random error
  • Leads to a loss of precision

54
Systematic Error
  • Defined as measurements that are consistently too
    high or too low, bias
  • Many causes, contaminated solutions,
    malfunctioning instruments, temperature
    fluctuations, etc., etc.

55
Systematic Error
  • Technician controls sources of systematic error
    and should try to eliminate them, if possible
  • Temperature effects
  • Humidity effects
  • Calibration of instruments
  • Etc.

56
Systematic Error
  • In the presence of systematic error, does it help
    to repeat measurements?

57
Systematic Error
  • Systematic error
  • Does impact accuracy
  • Repeating measurements with systematic error does
    not improve the accuracy of the measurements
    because the same error is always there

58
Without Systematic Error
MeanMedianMode true value
With Systematic Error
True Value
59
Another DefintionOf Error Is
  • Error is the difference between the measured
    value and the true value due to any cause
  • Absolute error True value - measured value
  • Percent error is
  • True value - measured value (100 )
  • True value

60
Errors AndUncertainty
  • Errors lead to uncertainty in measurements
  • Can never know the exact, true value for any
    measurement.
  • Idea of a true value is abstract never
    knowable.
  • In practice, get close enough

61
Uncertainty Is
  • Estimate of the inaccuracy of a measurement that
    includes both the random and systematic
    components.

62
Uncertainty Also Is
  • An estimate of the range within which the true
    value for a measurement lies, with a given
    probability level.

63
Uncertainty
  • Not surprisingly, it is difficult to state, with
    certainty, how much uncertainty there is in a
    measurement value.
  • But that doesnt keep metrologists from trying

64
Metrologists
  • Metrologists try to figure out all the possible
    sources of uncertainty and estimate their
    magnitude
  • One or another factor may be more significant.
    For example, when measuring very short lengths
    with micrometers, care a lot about repeatability.
    But, with measurements of longer lengths,
    temperature effects are far more important

65
Report Values
  • Metrologists come up with a value for uncertainty
  • You may see this in catalogues or specifications
  • Example
  • measured value an estimate of uncertainty

66
UncertaintyEstimates
  • Details are not important to us now
  • But principle is any measurement, need to know
    where the important sources of error might be

67
Significant Figures
  • One cause of uncertainty in all measurements is
    that the value for the measurement can only read
    to a certain number of places
  • This type of uncertainty. It is called
    resolution error.

68
Significant FigureConventions
  • Significant figure conventions are used to record
    the values from measurements
  • Expression of uncertainty
  • Also apply to very large counted values
  • Do not apply to exact values
  • Counts where you are certain of value
  • Conversion factors

69
Which RulerGives the Length of the Arrow With
More Certainty?
70
RoundingConventions
  • Use when combine numbers in calculations
  • Can be confusing
  • Look up rules when you need them

71
RecordingMeasured Values
  • Record measured values (or large counts) with
    correct number of significant figures
  • Dont add extra zeros dont drop ones that are
    significant
  • With digital reading, record exactly what it
    says assume the last value is estimated
  • With analog values, record all measured values
    plus one that is estimated
  • Discussed in Laboratory Exercise 1

72
Rounding
  • A Biotechnology company specifies that the level
    of RNA impurities in a certain product must be
    less than or equal to 0.02. If the level of RNA
    in a particular lot is 0.024, does that lot meet
    the specifications?

73
Rounding
  • The specification is set at thehundredth decimal
    place. Therefore, the result is rounded to that
    place when it is reported. The result rounded is
    therefore 0.02, and it meets the specification.

74
Rounding
  • Look at all the problems for chapter 13.

75
Good Web Site For Significant Figures
  • http//antoine.frostburg.edu/cgi-bin/senese/tutori
    als/sigfig/index.cgi

76
Match these descriptions with the 4
distributions in the figure
  • Good precision, poor accuracy
  • Good accuracy, poor precision
  • Good accuracy, good precision
  • Poor accuracy, poor precision

77
Thermometers
  • Each person should read the value from any of the
    six thermometers placed in the beaker in front of
    the class
  • Each person should record on the board the
    temperature of the water in the beaker, based on
    his/her own measurement
  • Do not consult other people

78
Thermometers
  • Look at the values for the thermometers on the
    board.
  • Do the numbers of figures recorded agree?
  • Significant figure conventions can guide us in
    how to record the value that we read off any
    measuring instrument.
  • With these thermometers, correct number of sig
    figs is _______.

79
Thermometers
  • Were the thermometers accurate?
  • Explain your answer
  • How could we figure out the true value for the
    temperature?

80
RepeatingMeasurements
  • Would repeating measurements with these
    thermometers, assuming we did not calibrate them,
    improve our ability to trust them?
  • Is their error an example of random or systematic
    error?

81
Calibration
  • Calibration of the thermometers could lead to
    increased accuracy
  • This is a type of systematic error
  • In the presence of systematic error, repeating
    the measurement will not improve its accuracy

82
Tolerance
  • Here is a catalog description of mercury
    thermometers.
  • Based on this description, are these thermometers
    out of the range for which their tolerance is
    specified?

83
Precision
  • Were they precise? How could precision be
    measured?
  • Would calibration help to make them more precise?

84
Calibration
  • Calibration would probably not improve their
    precision

85
Return To OurOriginal Type Of Question
  • Are our temperature measurements good
    measurements?
  • How do you make that judgment?
  • Can we trust them?

86
Thermometers Good Enough?
  • Are times that we need to be very close in
    temperature measurements. For example PCR is
    fairly picky.
  • Other times we can be pretty far off and process
    will still work.

87
Explore Some Of These Ideas
  • In lab
  • Calibrate instruments
  • Use standards
  • Check performance of pipettors
  • Record measurement values
  • Calculate per cent errors
  • Calculate repeatability
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