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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

Uncertainty in Measurement: Reading Instruments

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

Uncertainty: Confidence Intervals

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

Propagation of Uncertainty from Random Error

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

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Author Spotlight: Evaluating Clinicians' Adoption of Ultrasound-Guided Vascular Cannulation Through Simulation Training

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Twelve tips for clinicians dealing with uncertainty when assessing learners.

I Scott¹, A Gingerich², K W Eva¹

¹Centre for Health Education Scholarship (CHES), Department of Family Science, Faculty of Medicine, University of British Columbia , Canada.

Medical Teacher

|October 10, 2018

Summary

Clinician educators can manage assessment uncertainty by adapting clinical strategies. This article provides 12 tips to help educators navigate the distress of uncertainty in learner assessment.

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Area of Science:

Medical Education
Assessment in Healthcare
Clinician Development

Background:

Clinician educators experience distress due to uncertainty in student assessment.
Uncertainty is common in clinical practice, and clinicians develop strategies to manage it.
Less attention has been given to supporting clinician educators facing assessment uncertainty.

Purpose of the Study:

To provide guidance for clinician educators on managing uncertainty in assessment practices.
To translate effective clinical strategies for managing uncertainty into the educational assessment domain.
To offer practical advice through a '12 tips' format.

Main Methods:

Review and adaptation of strategies used by clinicians to manage uncertainty in patient care.
Application of these strategies to the context of assessing medical learners.
Development of a practical guide for clinician educators.

Main Results:

Identified parallels between clinical uncertainty and assessment uncertainty for educators.
Proposed translation of clinical coping strategies for educational assessment.
Offered 12 actionable tips for managing assessment-related uncertainty.

Conclusions:

Clinician educators can effectively manage assessment uncertainty by leveraging strategies from clinical practice.
Adapting clinical uncertainty management techniques can reduce educator distress and improve assessment quality.
Supporting clinician educators in navigating assessment uncertainty is crucial for medical education.