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

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...

Prediction Intervals

Prediction Intervals

The interval estimate of any variable is known as the prediction interval. It helps decide if a point estimate is dependable.
However, the point estimate is most likely not the exact value of the population parameter, but close to it. After calculating point estimates, we construct interval estimates, called confidence intervals or prediction intervals. This prediction interval comprises a range of values unlike the point estimate and is a better predictor of the observed sample value, y.

Wald-Wolfowitz Runs Test II

Wald-Wolfowitz Runs Test II

The Wald-Wolfowitz runs test, commonly referred to as the runs test, is a nonparametric test used to assess the randomness of ordered data. The test evaluates the number of runs, which are consecutive sequences of similar elements within the data. If the number of runs is significantly higher or lower than expected, the data is considered non-random, indicating a detectable pattern or structure.
For binary data, runs are identified using symbols such as + and −, or equivalently, 1s and 0s. In...

Confidence Intervals

Confidence Intervals

An unbiased point estimate is often insufficient to predict a population estimate, such as population mean or population proportion. In this scenario, a confidence interval is used. A confidence interval is an estimate similar to a sample proportion. However, unlike the point estimate which is a single value, the confidence interval contains a range of values. These values have lower and upper limits, known as confidence limits, and can be designated as L1 and L2, respectively.
A...

Wald-Wolfowitz Runs Test I

Wald-Wolfowitz Runs Test I

The Wald-Wolfowitz test, also known as the runs test, is a nonparametric statistical test used to assess the randomness of a sequence of two different types of elements (e.g., positive/negative values, successes/failures). It examines whether the order of the elements in a sequence is random or if there is a pattern or trend present. This nonparametric test applies to any ordered data despite the population and sample data distribution, even if a higher sample size is available.
The test works...

Power

Power

The concept of work involves force and displacement; meanwhile, the work-energy theorem relates the net work done on a body to the difference in its kinetic energy, calculated between two points on its trajectory. While none of these quantities or relations involves time explicitly, we know that the time available to accomplish work is often just as important as the amount of work itself. For example, sprinters in a race may have achieved the same velocity at the finish, therefore,...

You might also read

Related Articles

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

Sort by

Same author

Acute hypoxia impairs uphill running performance and alters metabolic responses in adult trained trail runners: A pilot study.

Physiological reports·2026

Same author

Where am I struggling? Detailed benchmarks for every workout and category in Hyrox© competition.

The Journal of sports medicine and physical fitness·2026

Same author

Decoding Neuromuscular Fatigue in Trail Running: A Systematic Review Across Distances and Sex Differences.

International journal of sports physiology and performance·2026

Same author

Hyrox©: A Descriptive Analysis of Participation Trends Among Over 275,000 Athletes in the New Fitness Modality.

Research quarterly for exercise and sport·2025

Same author

Does the terrain influence running critical power and biomechanics? An in-field study with highly trained trail runners.

European journal of applied physiology·2025

Same author

Editorial: Decoding endurance performance: from theory to practice.

Frontiers in sports and active living·2025

Search research articles

Related Experiment Video

Updated: Jan 22, 2026

The Power of Interstimulus Interval for the Assessment of Temporal Processing in Rodents

The Power of Interstimulus Interval for the Assessment of Temporal Processing in Rodents

Published on: April 19, 2019

How Does Power During Running Change when Measured at Different Time Intervals?

Felipe García-Pinillos¹, Víctor M Soto-Hermoso², Pedro Á Latorre-Román³

¹Department of Physical Education, Sports and Recreation, Universidad de La Frontera, Temuco, Chile.

International Journal of Sports Medicine

|July 12, 2019

Summary

Running power measurements using the Stryd™ system are stable and reliable across various recording intervals. Shorter intervals (10-120s) provide comparable running power data to longer intervals (180s).

More Related Videos

Measuring Sensitivity to Viewpoint Change with and without Stereoscopic Cues

Measuring Sensitivity to Viewpoint Change with and without Stereoscopic Cues

Published on: December 4, 2013

Power Input Measurements in Stirred Bioreactors at Laboratory Scale

Power Input Measurements in Stirred Bioreactors at Laboratory Scale

Published on: May 16, 2018

Related Experiment Videos

Last Updated: Jan 22, 2026

The Power of Interstimulus Interval for the Assessment of Temporal Processing in Rodents

The Power of Interstimulus Interval for the Assessment of Temporal Processing in Rodents

Published on: April 19, 2019

Measuring Sensitivity to Viewpoint Change with and without Stereoscopic Cues

Measuring Sensitivity to Viewpoint Change with and without Stereoscopic Cues

Published on: December 4, 2013

Power Input Measurements in Stirred Bioreactors at Laboratory Scale

Power Input Measurements in Stirred Bioreactors at Laboratory Scale

Published on: May 16, 2018

Area of Science:

Exercise Physiology
Sports Biomechanics

Background:

Accurate measurement of running power is crucial for training and performance analysis in endurance sports.
The impact of different data recording intervals on the reliability of running power metrics is not fully understood.

Purpose of the Study:

To investigate the variability of running power output measured by a Stryd™ power meter at different recording intervals.
To determine if shorter recording intervals affect the consistency of power data during continuous running.

Main Methods:

Forty-nine endurance runners completed a treadmill protocol at a self-selected comfortable velocity.
Running power was recorded using a Stryd™ power meter over six intervals (10s to 180s).
Statistical analyses included ANOVAs and Bland-Altman plots to assess differences and agreement between intervals.

Main Results:

No significant differences in power output magnitude were found between recording intervals (p=0.276).
An almost perfect association (ICC≥0.999) was observed for power output across all intervals.
Longer intervals showed slightly smaller systematic bias and random errors.

Conclusions:

Running power data from the Stryd™ system is a stable metric with practically negligible differences between short (10-120s) and long (180s) recording intervals.
The findings support the use of various recording intervals for reliable running power data analysis.