Measurement Uncertainities

1. Measurement
:
Uncertainties

2. Understanding and Communicating
Measurement uncertainty is a fundamental property of physics that arises from the
Heisenberg uncertainty principle. This principle states that it is impossible to precisely
measure both the position and momentum of a particle at the same time. This means
that even in the most controlled experiments, there is always some level of uncertainty
in the measurement.
The magnitude of this uncertainty depends on a variety of factors, such as the sensitivity
of the measuring instrument and the stability of the experimental conditions.
Understanding and accounting for measurement uncertainty is critical in order to ensure
that experimental results are reliable and accurate

3. ERRORS

4. Systematic and
random errors
Experimental errors in laboratory
measurements can be classified into
systematic errors (bias) and random errors
(precision).

5. Systematic errors are errors that arise from
a flaw or consistent deviation in the
measurement process. These errors can be
corrected by appropriate adjustments or
corrections to the measurement process.
Systematic
Random errors are unpredictable variations in
the measurement process that can cause
measurements to differ from each other. These
errors are associated with factors such as
environmental conditions or instrument
variability, and they can be analyzed
statistically
Random

6. Managing measurement uncertainties is a critical aspect of accurate and reliable scientific, engineering,
and industrial measurements. Here are some best practices for managing measurement uncertainties:
1.Understand the measurement process: Thoroughly understand the measurement process, including
the instruments, methods, and procedures being used. This includes understanding the limitations and
potential sources of error in the measurement process.
2.Identify sources of uncertainty: Identify all potential sources of uncertainty in the measurement
process, including random and systematic errors. Random errors are due to inherent variability in
measurements, while systematic errors are due to biases or inaccuracies in the measurement process.
Best Practices for Managing Measurement
Uncertainty

7. 3.Quantify uncertainty: Quantify the uncertainties associated with each potential source of error. This can be
done through statistical analysis, calibration data, or other methods. Express uncertainties using appropriate
units and include them in the measurement results.
4. Follow recognized standards and guidelines: Follow recognized standards and guidelines for measurement
uncertainty, such as the International Organization for Standardization (ISO) Guide to the Expression of
Uncertainty in Measurement (GUM) or other relevant standards specific to your field or industry.
5.Document and communicate uncertainties: Document all uncertainties associated with the measurement
process, including the methods used for quantifying them. Clearly communicate the uncertainties in
measurement results and reports to users, clients, or stakeholders to ensure proper interpretation and use of the
data.

8. Guide to the Expression of Uncertainty in
Measurement
“Uncertainty (of measurement) is a parameter
associated with the result of a measurement that
characterizes the dispersion of the values that could
reasonably be attributed to the measurand”
What is the use of GUM method ?
GUM method states that the uncertainty of a
measurement result must be propagated from the
uncertainty of each contributing factor

9. Types of uncertainty on the basis of
evaluation
Type A: Evaluation of uncertainty by statistical analysis of series of observations,
including quite complex least squares adjustments.
Type B: Evaluation of uncertainty by means other than statistical analysis,e.g. with
the use of estimates from previous measurements, specifications from the
manufacturer, hand-books,calibration certificates etc.

10. Types of uncertainties on the basis of stages
of calculations.
1 Standard Uncertainty
It is the uncertainity of individual measurements usually expressed in terms of the usual standard
deviation It is denoted by u(Y) where Y is a result of a measurement.
2 Combined Uncertainty
It is an application of the law of propagation of uncertainty in measurement on the function Y =
f(X1,X2, X3,...)
3 Expanded uncertainty
It is a quantity defining an interval about the result of a measurement. The fraction k is denoted
coverage probability or level of confidence. Last step

11. An example to the applicaiton of GUM
the length measurement is defined as the difference
between two measuring scales read from the Vernier
Calliper
Therefore
u(x1)= u(x2)= 0.1mm for a confidence
interval of 1
The 0.42 interval is the expanded
uncertainty U with expansion factor k=2
that covers 95.4% confidence interval
Y= X2 - X1 +- U(Y) = (2.5±0.42)mm

12. Reduce Uncertainty In Measurement
What is Uncertainty in Measurement
An error is the discrepancy between a measured value and the actual or true
value. Uncertainty is the effect of many errors. This effect may manifest itself
as the variability in replicate determinations of the measurand, or, as 'inherited'
variability within a single component of the measurand.
Reducing Uncertainty describes what Intelligence Community analysts do,
how they do it, and how they are affected by the political context that shapes,
uses, and sometimes abuses their output.

13. To Reducing the Uncertainty by Following
Steps -
Validate the measurements
by checking them repeatedly
or use other kinds of
validation methods.distante
do Sol
Choose the best instrument for
measurement and use
calibration facilities with a
minimum number of errors.

14. THANK YOU