3. EDef

# 3. EDef - Uncertainty Analysis I Quantifying the unknown...

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Uncertainty Analysis I Quantifying the unknown and the unknowable

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Definitions I: Error • The error, E , is the difference between the true value, x , and a measured value, x i : • Since, x is unknown, then so is E . •A lw ay s . i E xx =
Definitions II: Uncertainty • For multiple measurements, a mean value, , can be estimated, hence: • Since x remains unknown, then E is still unknown. • Uncertainty , u x , x , is an estimate of E . x E xx =

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Classification of errors • Systematic bias, may be measured and corrected. • Random. The likely magnitude of the remaining error must be estimated. • Use the larger of: ( i ) instrument resolution, ( ii ) standard deviation, ( iii ) precision. •( ii ) & ( iii ) require multiple measurements
Single sample uncertainty I Imagine a ruler with two scale resolutions: δ x 1 δ x 2 • Suppose the scale marks exactly represent the limit of our ability to locate the blob. We may say only which mark is closest.

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3. EDef - Uncertainty Analysis I Quantifying the unknown...

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