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In analytical chemistry, we often perform repetitive measurements to detect and minimize inaccuracies caused by both determinate and indeterminate errors. Despite the cares we take, the presence of random errors means that repeated measurements almost never have exactly the same magnitude. The collective difference between these measurements - observed values - and the estimated or expected value is called uncertainty. Uncertainty is conventionally written after the estimated or expected value.

It is important to express the uncertainty with the correct number of significant figures, which is the number of digits required to represent the precise outcome. The magnitude of possible variations from the significant figure in either direction is expressed as addition or subtraction to the significant figure. Uncertainty represented in this way is called absolute uncertainty. The ratio of absolute uncertainty to the magnitude of the estimated or expected value is known as relative uncertainty.

Tags
UncertaintyAnalytical ChemistryMeasurementsDeterminate ErrorsIndeterminate ErrorsRandom ErrorsSignificant FiguresAbsolute UncertaintyRelative UncertaintyExpected ValueObserved Values

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1.9 : Uncertainty: Overview

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1.1 : SI Units: 2019 Redefinition

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1.2 : Degrees of Freedom

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1.3 : Statistical Analysis: Overview

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1.4 : Types of Errors: Detection and Minimization

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1.5 : Systematic Error: Methodological and Sampling Errors

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1.6 : Random Error

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1.7 : Standard Deviation of Calculated Results

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1.8 : Introduction to z Scores

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1.10 : Propagation of Uncertainty from Random Error

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1.11 : Propagation of Uncertainty from Systematic Error

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1.12 : Uncertainty: Confidence Intervals

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1.13 : Significance Testing: Overview

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1.14 : Identifying Statistically Significant Differences: The F-Test

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1.15 : Comparing Experimental Results: Student's t-Test

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