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

Sample Size Calculation

Sample Size Calculation

Knowledge of the sample size is the first requirement to conduct random sampling or an experiment. The sample size is the total number of units, observations, or groups (in some cases) used to get the data to estimate a population parameter. As the name suggests, the sample size is that of the sample drawn from the population and differs from the population size.
The sample size for the given experiment or sampling effort is fundamental to any study design. Sample size decides the number of...

Methods of Medium Optimization

Methods of Medium Optimization

Optimizing growth media enhances microbial proliferation and maximizes product yield. Statistical experimental design methodologies provide structured and reproducible approaches, offering progressively higher levels of robustness and efficiency.The One-Factor-at-a-Time (OFAT) MethodThe One-Factor-at-a-Time (OFAT) method involves adjusting a single variable while keeping all others constant. However, it cannot detect interactions between variables, often leading to suboptimal outcomes when...

One-Way ANOVA: Equal Sample Sizes

One-Way ANOVA: Equal Sample Sizes

One-Way ANOVA can be performed on three or more samples with equal or unequal sample sizes. When one-way ANOVA is performed on two datasets with samples of equal sizes, it can be easily observed that the computed F statistic is highly sensitive to the sample mean.
Different sample means can result in different values for the variance estimate: variance between samples. This is because the variance between samples is calculated as the product of the sample size and the variance between the...

Testing a Claim about Population Proportion

Testing a Claim about Population Proportion

A complete procedure for testing a claim about a population proportion is provided here.
There are two methods of testing a claim about a population proportion: (1) Using the sample proportion from the data where a binomial distribution is approximated to the normal distribution and (2) Using the binomial probabilities calculated from the data.
The first method uses normal distribution as an approximation to the binomial distribution. The requirements are as follows: sample size is large...

One-Way ANOVA: Unequal Sample Sizes

One-Way ANOVA: Unequal Sample Sizes

One-way ANOVA can be performed on three or more samples of unequal sizes. However, calculations get complicated when sample sizes are not always the same. So, while performing ANOVA with unequal samples size, the following equation is used:

Survival Tree

Survival Tree

Survival trees are a non-parametric method used in survival analysis to model the relationship between a set of covariates and the time until an event of interest occurs, often referred to as the "time-to-event" or "survival time." This method is particularly useful when dealing with censored data, where the event has not occurred for some individuals by the end of the study period, or when the exact time of the event is unknown.
Building a Survival Tree
Constructing a...

You might also read

Related Articles

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

Sort by

Same author

A novel radiological score on digital subtraction angiography predicts prognosis for acute basilar artery occlusion treated with endovascular thrombectomy: a two-center retrospective study.

BMC neurology·2025

Same author

Enhancing Taekwondo performance: The role of pre-kicking techniques and stimulus triggers in elite athletes.

Journal of sports sciences·2025

Same author

Positive 14-3-3 protein in cerebrospinal fluid followed by poppy-induced delayed post-hypoxic leukoencephalopathy: A case report.

Heliyon·2024

Same author

Unilateral peroneal neuropathy in a patient following laparoscopic sleeve gastrectomy.

Postgraduate medicine·2024

Same author

Optical Coherence Tomography-Guided Stenting for Common Carotid Free-Floating Thrombus.

Journal of endovascular therapy : an official journal of the International Society of Endovascular Specialists·2024

Same author

Automating Video-Based Two-Dimensional Motion Analysis in Sport? Implications for Gait Event Detection, Pose Estimation, and Performance Parameter Analysis.

Scandinavian journal of medicine & science in sports·2024

Same journal

The association between habitual physical activity and sitting-induced endothelial dysfunction.

Journal of sports sciences·2026

Same journal

Rational and irrational fan beliefs and psychological distress in football fans: The moderating role of gender, marital status, and match outcome.

Journal of sports sciences·2026

Same journal

The interaction effects of flight distance, scheduling and contextual factors on basketball performance.

Journal of sports sciences·2026

Same journal

Comparing the effects of small-sided games, skill development, and plyometric training on basketball learning and athletic performance in youth male athletes: A quasi-experimental study.

Journal of sports sciences·2026

Same journal

The effect of sport-specific virtual reality training for soccer players on cognitive performance and related brain processing.

Journal of sports sciences·2026

Same journal

Physical activity as a moderator between problematic social media use and mental health in adolescents.

Journal of sports sciences·2026

See all related articles

Search research articles

Related Experiment Video

Updated: Apr 26, 2026

Barnes Maze Testing Strategies with Small and Large Rodent Models

Barnes Maze Testing Strategies with Small and Large Rodent Models

Published on: February 26, 2014

Determining optimal trial size using sequential analysis.

Paul Geoffrey Taylor¹, Kwee-Yum Lee, Raul Landeo

¹a Australian Catholic University , Australia.

Journal of Sports Sciences

|August 2, 2014

Summary

This summary is machine-generated.

Determining the optimal number of trials for human movement analysis is crucial. Sequential analysis suggests 20 trials are preferred for stable kinematic data in overarm throwing, with 13-17 trials ensuring reliable means.

Keywords:

kinematic profile mean stability overarm throw sequential analysis trial size

More Related Videos

The Innovation Arena: A Method for Comparing Innovative Problem-Solving Across Groups

The Innovation Arena: A Method for Comparing Innovative Problem-Solving Across Groups

Published on: May 13, 2022

Author Spotlight: Evaluating the Adjuvant Efficacy and Safety of Angong Niuhuang Pill in Viral Encephalitis Treatment

Author Spotlight: Evaluating the Adjuvant Efficacy and Safety of Angong Niuhuang Pill in Viral Encephalitis Treatment

Published on: April 19, 2024

Related Experiment Videos

Last Updated: Apr 26, 2026

Barnes Maze Testing Strategies with Small and Large Rodent Models

Barnes Maze Testing Strategies with Small and Large Rodent Models

Published on: February 26, 2014

The Innovation Arena: A Method for Comparing Innovative Problem-Solving Across Groups

The Innovation Arena: A Method for Comparing Innovative Problem-Solving Across Groups

Published on: May 13, 2022

Author Spotlight: Evaluating the Adjuvant Efficacy and Safety of Angong Niuhuang Pill in Viral Encephalitis Treatment

Author Spotlight: Evaluating the Adjuvant Efficacy and Safety of Angong Niuhuang Pill in Viral Encephalitis Treatment

Published on: April 19, 2024

Area of Science:

Biomechanics
Human Movement Analysis
Sports Science

Background:

Characterizing typical human movement profiles requires stable statistical means.
Sequential analysis is a method to determine the number of trials needed for data stability.
The arbitrary selection of trial numbers in sequential analysis can impact results.

Purpose of the Study:

To investigate the effect of different total trial numbers on sequential analysis results.
To determine the optimal number of trials for stable kinematic data in overarm throwing.
To establish the number of trials required for stability in discrete and time-series kinematic data.

Main Methods:

Twenty participants performed 30 trials of overarm throwing.
Sequential analyses were applied to three-dimensional (3-D) kinematic data using 10, 20, and 30 trial numbers.
Moving point means were assessed against a set bandwidth to determine stability.

Main Results:

A total of 20 trials was found to be the preferred number for sequential analyses.
Groups using 10 trials consistently produced erroneous results.
Moving point means remained statistically unchanged after the 10th trial.
A trial size between 13 and 17 trials provides stable means for overarm throwing kinematics.

Conclusions:

The number of trials analyzed significantly impacts the reliability of sequential analysis in human movement studies.
For overarm throwing kinematics, approximately 13-17 trials are recommended to achieve stable means.
Future research should consider the optimal number of trials to ensure accurate characterization of human movement profiles.