Search research articles

ABOUT JoVE

Overview Leadership Blog JoVE Help Center

AUTHORS

Publishing Process Editorial Board Scope & Policies Peer Review FAQ Submit

LIBRARIANS

Testimonials Subscriptions Access Resources Library Advisory Board FAQ

RESEARCH

JoVE Journal Methods Collections JoVE Encyclopedia of Experiments Archive

EDUCATION

JoVE Core JoVE Business JoVE Science Education JoVE Lab Manual Faculty Resource Center Faculty Site

Terms & Conditions of Use

Related Concept Videos

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...

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: 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...

Interval Level of Measurement

Interval Level of Measurement

For effective statistical analysis, data are classified into four levels of measurement—nominal, ordinal, interval, and ratio.
Data measured using the interval scale are similar to ordinal level data because they have a definite arrangement. However, in the interval level of measurement, the differences between data values are meaningful even though the data does not have a starting point.
Temperature is measured using the interval scale. It is measurable data, and the difference between...

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...

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by

Same author

Systematic bias in point-of-care INR testing: comparative analysis of Abbott and Roche devices.

Clinical chemistry and laboratory medicine·2026

Same author

Addressing property and unit discordance in laboratory interoperability: the role of NPU as a governance layer.

Clinical chemistry and laboratory medicine·2026

Same author

What are the correlates of laboratory productivity in clinical laboratories in the Asia Pacific region?

Clinical biochemistry·2026

Same author

An improved approach to modelling patient reclassification: HbA<sub>1c</sub> as an example.

Clinical chemistry and laboratory medicine·2026

Same author

The value of external quality assurance programs in identifying shifts in high-sensitivity troponin assays: a case for careful selection of low-level target concentrations.

Pathology·2026

Same author

An analysis of 10 years of synovial fluid crystal external quality assurance data.

Pathology·2026

Search research articles

Related Experiment Video

Updated: Apr 30, 2026

Split Point Analysis and Uncertainty Quantification of Thermal-Optical Organic/Elemental Carbon Measurements

Split Point Analysis and Uncertainty Quantification of Thermal-Optical Organic/Elemental Carbon Measurements

Published on: September 7, 2019

The relationship between measurement uncertainty and reporting interval.

Tony Badrick¹, Robert C Hawkins²

¹Faculty of Health Science and Medicine, Bond University, Australia tbadrick@bond.edu.au.

Annals of Clinical Biochemistry

|May 14, 2014

Summary

Measurement uncertainty (MU) is crucial for interpreting lab results. This study shows how MU can optimize the reporting interval, ensuring accuracy and reflecting analytical performance for better clinical decisions.

Keywords:

Statistics laboratory management laboratory statistics measurement uncertainty reporting unit

More Related Videos

Measurement of Spatial Stability in Precision Grip

Measurement of Spatial Stability in Precision Grip

Published on: June 4, 2020

Precision of In Vivo Quantitative Tooth Wear Measurement Using Intra-Oral Scans

Precision of In Vivo Quantitative Tooth Wear Measurement Using Intra-Oral Scans

Published on: July 12, 2022

Related Experiment Videos

Last Updated: Apr 30, 2026

Split Point Analysis and Uncertainty Quantification of Thermal-Optical Organic/Elemental Carbon Measurements

Split Point Analysis and Uncertainty Quantification of Thermal-Optical Organic/Elemental Carbon Measurements

Published on: September 7, 2019

Measurement of Spatial Stability in Precision Grip

Measurement of Spatial Stability in Precision Grip

Published on: June 4, 2020

Precision of In Vivo Quantitative Tooth Wear Measurement Using Intra-Oral Scans

Precision of In Vivo Quantitative Tooth Wear Measurement Using Intra-Oral Scans

Published on: July 12, 2022

Area of Science:

Clinical Chemistry
Laboratory Medicine
Measurement Science

Background:

Measurement uncertainty (MU) is vital for clinical interpretation and laboratory quality control.
MU is not commonly used to set appropriate analyte reporting intervals.
This study explores the link between MU and analyte reporting intervals.

Purpose of the Study:

To establish the relationship between measurement uncertainty and analyte reporting intervals.
To propose a method for optimizing reporting intervals based on MU.

Main Methods:

Defined reporting interval (R) as the smallest clinical reporting unit.
Established that reference change values and expanded MU must be calculable.
Determined the upper limit for R using expanded MU: R ≤ k·SDa/1.9.

Main Results:

Expanded MU offers a stricter criterion for setting the upper limit of the reporting interval.
The formula R ≤ k·SDa/1.9 provides a quantitative method for determining the appropriate reporting interval.

Conclusions:

Utilizing MU estimates for reporting intervals aligns practices with analytical capabilities.
This approach acknowledges the inherent error in laboratory measurements.