Knowledge of the uncertainty of measurement of testing and calibration results is fundamentally important for laboratories, their clients and all institutions using these results for comparative purposes. Uncertainty of measurement is a very important metric of the quality of a result or a testing method. Main points covered: • To introduce the basic concepts related to measurement results and measurement uncertainty • Explain the relevance of these concepts to chemical analysis data • Introduce mathematical concepts, uncertainty sources and important approaches for estimation of measurement uncertainty Presenter: This webinar was presented by Dotun Bolade, who is an Analytical Chemist/Environmental Scientist by training and practice with years of experience in laboratory instrumentation and automation. For him, ISO management systems have become second nature having worked in environments where ISO 9001, 14001, 18001 and 17025 have been fully implemented. He is a Certified PECB ISO/IEC 17025 Lead Assessor. Link of the recorded session published on YouTube: https://youtu.be/AOpFou7_FVI

1. ESTIMATION OF MEASUREMENT
UNCERTAINTY:
A REQUIREMENT FOR ISO 17025
ACCREDITATION

2. Dotun Bolade
Managing Consultant
Dotun Bolade is an Analytical Chemist/Environmental Scientist by training
and practice has spent the past five years working in Nigeria’s Oil and Gas
industry. For him, ISO management systems have become second nature
having worked in environments where ISO 9001, 14001, 18001 and 17025
have been fully implemented/accredited. He is a Certified PECB ISO/IEC
17025 Lead Assessor, ISO 14001, 9001 & 29001 Lead Implementer and
Certified Trainer. Dotun is a PECB Partner and Managing Consultant,
EN2SOL PNP LIMITED.
Contact Information
2348066884793
Dotun.bolade@energysolutiosng.com
www.domain.com
linkedin.com/Dotun Bolade
twitter.com/dotunBolade

3. Objectives:
 To introduce the basic concepts related to measurement
results and measurement uncertainty & their relevance to
chemical data
 Introduce mathematical concepts, uncertainty sources and
important approaches for estimation of measurement
uncertainty
 Understand availability and relevance of data in estimating
measurement uncertainty
 Understand selection of suitable approach for uncertainty
measurement based on available data

4. Content:
 Introduction
 Accuracy, Precision &
Trueness
 Sources of Uncertainty
in Measurement
 Concepts in
Uncertainty estimation
 Elements of an
Uncertainty Budget
 Uncertainty
Calculation in
Pipetting; an
example
 References

5. Introduction:
Key Terms:
 Measurement/Chemical Analysis
 Uncertainty/Uncertainty Range
 Measurand
 True Value
 Measured Value
 Error (systematic & random)

6. Accuracy, Precision & Trueness:

7. Common Sources of Uncertainty in
Measurement:
 Equipment
 Unit Under Test
 Operator
 Method
 Calibration
 Environment
Uncertainty in
Volumetric
Measurements:
o Repeatability Uncertainty
o Calibration Uncertainty
o Temperature Uncertainty
o Application-Specific
Uncertainty

8. Concepts in Uncertainty Estimation:
 Normal Distribution

9. Concepts in Uncertainty Estimation:
 T-Distribution

10. Elements of an Uncertainty Budget:
 Repeatability
 Reproducibility
 Stability
 Bias
 Drift
 Resolution
 Reference Standard
 Reference Standard
Stability
To calculate Repeatability:
 Repeat a measurement
‘n’ number of times
 Record the results of
each measurement.
 Calculate the standard
deviation.

11. Reproducibility:
Common comparisons for Reproducibility Testing:
Operator vs Operator Reproducibility
Equipment vs Equipment Reproducibility
Method vs Method Reproducibility
Day vs Day Reproducibility
Environment vs Environment Reproducibility
To calculate Reproducibility:
 Perform a Repeatability Test
 Calculate the mean of average
 Change a variable and repeat the Repeatability Test
 Calculate the mean or average.
 Calculate the standard deviation of the test averages

12. Stability:
Property of a measuring instrument,
whereby its metrological properties
remain constant in time
To calculate Stability:
 Review your last 3 calibration reports
 Record the results from each calibration report
 Calculate the standard deviation of the
calibration results.

13. Bias:
 Estimate of systematic measurement error
 Average of replicate indication minus a
reference quantity value
To calculate Bias:
 Review your latest calibration report
 Find the As Left value or measurement result
 Find the Nominal value or standard value
 Calculate the difference.

14. Drift:
 Continuous or incremental change over time
in indication, due to changes in metrological
properties of a measuring instrument
To calculate Drift:
 Review your last 3 calibration reports
 Record the results from each calibration report
 Record the date each calibration was performed
 Calculate the average daily drift rate
 Multiply the average daily drift rate by your
calibration interval (in days).

15. Resolution:
 Smallest change in a quantity being
measured that causes a perceptible change
in the corresponding indication
To Find Resolution:
 Look at your measurement system or
equipment
 Find the least significant digit
 Observe the smallest incremental change

16. Reference Standard Uncertainty:
 Uncertainty of a measurement standard designated for
the calibration of other measurement standards for
quantities of a given kind in a given organization or at a
given location
 Reference standard uncertainty should be included in
the every uncertainty budget.
To Calculate Reference Standard Uncertainty:
 Review your latest calibration report
 Find the reported estimate of measurement
uncertainty

17. Reference Standard Stability:
 stability of a measurement standard designated for the
calibration of other measurement standards for
quantities of a given kind in a given organization or at a
given location
 Reference standard uncertainty should be included in
the every uncertainty budget.
To Calculate Reference Standard Stability:
 Review your last 3 calibration reports
 Record the uncertainty estimate from each calibration report
 Calculate the standard deviation.

18. Uncertainty Calculation in Pipetting:

19. Uncertainty Calculation in Pipetting:
In calculating the volume and Uncertainty of
liquid delivered from a self-calibrated volumetric
pipette, there are 3 main uncertainty
components;
Uncertainty due to repeatability, u(V,rep)
Uncertainty due to pipette calibration, u(V,cal)
Uncertainty due to the temperature difference
from 20 °C, u(V,temp).

20. Uncertainty Calculation in Pipetting:
In calculating the volume and Uncertainty of
liquid delivered from a self-calibrated volumetric
pipette, there are 3 main uncertainty
components;
Uncertainty due to repeatability, u(V,rep)
Uncertainty due to pipette calibration, u(V,cal)
Uncertainty due to the temperature difference
from 20 °C, u(V,temp).

21. Uncertainty Calculation in Pipetting:
Uncertainty due to
repeatability of
pipetting u (V, REP)
is equal to this
standard deviation
0.0057 ml

22. Uncertainty Calculation in Pipetting:
Uncertainty of the calibration is
expressed (when calibration is done)
as the standard deviation of the mean:

23. Uncertainty Calculation in Pipetting:
When there is a possibility that pipetting is
performed at a different temperature from
the calibration (and this possibility exists
almost always), then an additional
uncertainty source due to temperature
change is introduced and it has to be taken
into account.

24. Uncertainty Calculation in Pipetting:
Combined Standard Uncertainty:
When estimating the standard uncertainty of an
output quantity then the standard uncertainties of all
input quantities are taken into account
The standard uncertainty of the output quantity
obtained in this way is called combined standard
uncertainty

25. Uncertainty Calculation in Pipetting:
Expanded Uncertainty:
• Expanded uncertainty is calculated from the
standard uncertainty by multiplying it with
a coverage factor, k.
• In the case of the pipetting example the k = 2
expanded uncertainty is found as follows:
U(V ) = uc(V ) · k = 0.0077 · 2 = 0.0154 ml

26. Uncertainty Calculation in Pipetting:
Summary:
The volume of the pipetted liquid is:
V = (9.992 ± 0.015) ml, k = 2, norm
The parentheses (brackets) mean that the unit “ml” is valid
both for the value and the uncertainty. “norm.” means that
the output quantity is expected to be approximately
normally distributed. This, together with coverage factor
value 2, means that the presented uncertainty is expected to
corresponds to approximately 95% coverage probability

27. References:
• A2LA. (2015). R205 – Specific Requirements: Calibration
Laboratory Accreditation Program. Frederick: A2LA.
• JCGM. (2012). International Vocabulary of Metrology:
Basic and General Concepts and Associated Terms. Sèvres:
BIPM.
• Estimation of Measurement Uncertainty in Chemical
Analysis. Available at https://sisu.ut.ee/measurement/10-
approach-based-validation-and-quality-control-data-top-
down-approach

28. ISO 17025 Training Courses
 ISO/IEC 17025 Introduction
1 Day Course
 ISO/IEC 17025 Foundation
2 Days Course
 ISO/IEC 17025 Lead Implementer
5 Days Course
 ISO/IEC 17025 Lead Assessor
5 Days Course
Exam and certification fees are included in the training price.
https://pecb.com/iso-iec-17025-lead-assessor | www.pecb.com/events

29. THANK YOU
?
2348066884793
dotun.bolade@energysolutionsng.com
linkedin.com/Dotun Bolade
twitter.com/dotunBolade
oladotunbolade@gmail.com