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The Uncertainty Principle

The Uncertainty Principle

Werner Heisenberg considered the limits of how accurately one can measure properties of an electron or other microscopic particles. He determined that there is a fundamental limit to how accurately one can measure both a particle’s position and its momentum simultaneously. The more accurate the measurement of the momentum of a particle is known, the less accurate the position at that time is known and vice versa. This is what is now called the Heisenberg uncertainty principle. He...

Uncertainty in Measurement: Reading Instruments

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Counting is the type of measurement that is free from uncertainty, provided the number of objects being counted does not change during the process. Such measurements result in exact numbers. By counting the eggs in a carton, for instance, one can determine exactly how many eggs are there in the carton. Similarly, the numbers of defined quantities are also exact. For example, 1 foot is exactly 12 inches, 1 inch is exactly 2.54 centimeters, and 1 gram is exactly 0.001 kilograms. Quantities...

Uncertainty: Overview

Uncertainty: Overview

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.

Uncertainty in Measurement: Significant Figures

Uncertainty in Measurement: Significant Figures

All the digits in a measurement, including the uncertain last digit, are called significant figures or significant digits. Note that zero may be a measured value; for example, if a scale that shows weight to the nearest pound reads “140,” then the 1 (hundreds), 4 (tens), and 0 (ones) are all significant (measured) values.

Uncertainty: Confidence Intervals

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The confidence interval is the range of values around the mean that contains the true mean. It is expressed as a probability percentage. The interpretation of a 95% confidence interval, for instance, is that the statistician is 95% confident that the true mean falls within the interval. The upper and lower limits of this range are known as confidence limits. The confidence limits for the true mean are estimated from the sample's mean, the standard deviation, and the statistical factor...

Propagation of Uncertainty from Random Error

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An experiment often consists of more than a single step. In this case, measurements at each step give rise to uncertainty. Because the measurements occur in successive steps, the uncertainty in one step necessarily contributes to that in the subsequent step. As we perform statistical analysis on these types of experiments, we must learn to account for the propagation of uncertainty from one step to the next. The propagation of uncertainty depends on the type of arithmetic operation performed on...

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Related Experiment Video

Updated: Feb 4, 2026

Assessing the Coherence of Parents' Short Narratives Regarding their Child Using the Five-Minute Speech Sample Procedure

Assessing the Coherence of Parents' Short Narratives Regarding their Child Using the Five-Minute Speech Sample Procedure

Published on: September 19, 2019

Child with multiple problems: Clinical complexity and uncertainty.

Michael McDowell^1,2,3

¹School of Medicine, University of Queensland, Brisbane, Queensland, Australia.

Journal of Paediatrics and Child Health

|October 9, 2018

Summary

Navigating complex cases in neurodevelopmental-behavioural paediatrics requires clinicians to manage uncertainty effectively. This involves using shared hypotheses about biological, developmental, and transactional factors to guide patient care.

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Last Updated: Feb 4, 2026

Assessing the Coherence of Parents' Short Narratives Regarding their Child Using the Five-Minute Speech Sample Procedure

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Published on: September 19, 2019

Making MR Imaging Child's Play - Pediatric Neuroimaging Protocol, Guidelines and Procedure

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An Objective and Child-friendly Assessment of Arm Function by Using a 3-D Sensor

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Published on: February 12, 2018

Area of Science:

Neurodevelopmental-behavioural paediatrics
Clinical practice

Background:

Clinicians face challenges interpreting research evidence in daily practice.
Childhood neurodevelopmental disorders present with inherent complexity, heterogeneity, and comorbidity.
Uncertainty is a constant factor due to individual social contexts.

Purpose of the Study:

To examine the clinical challenges in neurodevelopmental-behavioural paediatrics.
To offer strategies for effectively managing complexity and uncertainty.
To promote efficient clinical decision-making within knowledge limitations.

Main Methods:

Conceptual analysis of clinical challenges.
Proposal of a hypothesis-driven approach.
Emphasis on systematic testing and revision of clinical hypotheses.

Main Results:

Effective management of uncertainty is prioritized over its elimination.
A framework is suggested for addressing complexity by considering biological, developmental, and transactional components.
Hypotheses are proposed as shared tools within the child's care system.

Conclusions:

Clinicians should embrace uncertainty as inherent to practice.
A systematic, hypothesis-testing approach aids in longitudinal care.
Integrating biological, developmental, and transactional factors improves patient management.