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Uncertainty in Measurement: Accuracy and Precision

Uncertainty in Measurement: Accuracy and Precision

Scientists typically make repeated measurements of a quantity to ensure the quality of their findings and to evaluate both the precision and the accuracy of their results. Measurements are said to be precise if they yield very similar results when repeated in the same manner. A measurement is considered accurate if it yields a result that is very close to the true or the accepted value. Precise values agree with each other; accurate values agree with a true value.

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...

Random and Systematic Errors

Random and Systematic Errors

Scientists always try their best to record measurements with the utmost accuracy and precision. However, sometimes errors do occur. These errors can be random or systematic. Random errors are observed due to the inconsistency or fluctuation in the measurement process, or variations in the quantity itself that is being measured. Such errors fluctuate from being greater than or less than the true value in repeated measurements. Consider a scientist measuring the length of an earthworm using a...

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Updated: May 8, 2026

Combining Single-molecule Manipulation and Imaging for the Study of Protein-DNA Interactions

Combining Single-molecule Manipulation and Imaging for the Study of Protein-DNA Interactions

Published on: August 27, 2014

Quantifying experimental errors in measuring colloidal interaction potentials with optical tweezers.

José Muñetón-Díaz¹, Augustin Muster¹, Luis S Froufe-Pérez¹

¹Department of Physics, University of Fribourg, 1700 Fribourg, Switzerland. frank.scheffold@unifr.ch.

|September 16, 2025

Summary

This summary is machine-generated.

This study introduces a new framework to precisely measure particle interactions using optical tweezers (OT). By quantifying and correcting key experimental errors, it improves the accuracy of interaction potential measurements.

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Direct Force Measurements of Subcellular Mechanics in Confinement using Optical Tweezers

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Published on: August 31, 2021

Area of Science:

Colloid and Interface Science
Optical Physics
Nanotechnology

Background:

Accurate measurement of inter-particle potentials is crucial for understanding colloidal systems.
Existing optical tweezers (OT) methods are affected by unquantified experimental errors.
Previous studies acknowledged but did not thoroughly examine individual error effects.

Purpose of the Study:

To develop and validate a systematic framework for modeling and quantifying experimental errors in OT-based potential measurements.
To decouple and independently control key error sources: z-motion, dynamic, and static errors.
To enhance the precision and reliability of interaction potential measurements using optical tweezers.

Main Methods:

Development of a theoretical framework to model z-motion, dynamic, and static errors.
Controlled experiments to validate the error modeling framework.
Systematic tuning of experimental parameters to decouple and quantify individual error sources.

Main Results:

Demonstrated that the three key experimental errors can be independently controlled and accounted for.
Developed a method to reduce measurement ambiguities and improve accuracy compared to theoretical models.
Successfully applied the correction method to extract physically meaningful depletion attraction potentials.

Conclusions:

The presented framework offers a robust methodology for enhancing the accuracy of OT-based potential measurements.
This approach significantly improves the study of colloidal interactions by providing more reliable data.
Enables more accurate comparisons between experimental results and theoretical predictions.