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

Testing a Claim about Mean: Known Population SD

Testing a Claim about Mean: Known Population SD

A complete procedure of testing the hypothesis about a population mean is explained here.
Estimating a population mean requires the samples to be distributed normally. The data should be collected from the randomly selected samples having no sampling bias. The sample size needed to be higher than 30, and most importantly, the population standard deviation should be already known.
In most realistic situations, the population standard deviation is often unknown, but in rare circumstances, when it...

Statistical Significance

Statistical Significance

Once data is collected from both the experimental and the control groups, a statistical analysis is conducted to find out if there are meaningful differences between the two groups. A statistical analysis determines how likely any difference found is due to chance (and thus not meaningful). In psychology, group differences are considered meaningful, or significant, if the odds that these differences occurred by chance alone are 5 percent or less. Stated another way, if we repeated this...

Statistical Hypothesis Testing

Statistical Hypothesis Testing

Hypothesis testing is a critical statistical procedure facilitating informed, evidence-based decisions. It begins with a hypothesis, which is a tentative explanation, or a prediction about a population parameter. This hypothesis can be either a null hypothesis (H0), indicating no effect or difference, or an alternative hypothesis (Ha), suggesting an effect or difference.
Statistical significance measures the probability that an observed result occurred by chance. If this probability, known as...

You might also read

Related Articles

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

Sort by

Same author

Quantitative analysis of posterior chamber morphology on vault after ICL implantation: a retrospective paired study.

International journal of ophthalmology·2026

Same author

Focus on sex hormone axis disorder: exploring the susceptibility mechanism of dry eye in perimenopausal women.

Frontiers in medicine·2026

Same author

Three-dimensional choroidal parameter differences in myopic anisometropia.

BMC ophthalmology·2025

Same author

Dynamically covalent lipid nanoparticles mediate CRISPR-Cas9 genome editing against choroidal neovascularization in mice.

Science advances·2025

Same author

Self-assembling supramolecular columnar organogels formed by wedge shaped cesium 3,4,5-alkyloxy benzene sulfonates.

Soft matter·2025

Same author

Sleep quality according to chronotype in nurses working 8-hour shifts.

Occupational medicine (Oxford, England)·2024

Same journal

Assessment of freshness and oxidative stability of chicken meat patties at refrigerated storage using Dillenia indica peel powder: A natural substitute for synthetic antioxidants.

Poultry science·2026

Same journal

Blood acid/base balance in poultry: Dietary, environmental, and physiological determinants and emerging diagnostic opportunities.

Poultry science·2026

Same journal

Corrigendum to "Avian herpesvirus-specific LORF5 is a late gene,interacts with 19 viral and 111 host proteins, critical for virulence of Duck plague virus" [Poultry Science, Volume 105, Issue 7, July 2026, 106924].

Poultry science·2026

Same journal

Assessing the impact of dietary interventions on the resistomes of broiler chickens.

Poultry science·2026

Same journal

Pasture-based versus conventional broiler chicken production: Enterprise budget modeling and profitability analysis.

Poultry science·2026

Same journal

Characterizing locomotor behavior variability in commercial broiler flocks using large-scale video tracking.

Poultry science·2026

See all related articles

Search research articles

Related Experiment Video

Updated: May 8, 2026

Probing the Limits of Egg Recognition Using Egg Rejection Experiments Along Phenotypic Gradients

Probing the Limits of Egg Recognition Using Egg Rejection Experiments Along Phenotypic Gradients

Published on: August 22, 2018

Interpreting experiments on egg production--statistical considerations.

L Billard¹, E Song, M Y Shim

¹Department of Statistics, University of Georgia, Athens, GA 30602, USA.

Poultry Science

|August 21, 2013

Summary

This summary is machine-generated.

Correctly analyzing experimental data requires matching the analysis to the study design. This tutorial explains how to adjust analyses for covariates in factorial and repeated measures designs, using egg production data as an example.

More Related Videos

In Ovo Feeding of Commercial Broiler Eggs: An Accurate and Reproducible Method to Affect Muscle Development and Growth

In Ovo Feeding of Commercial Broiler Eggs: An Accurate and Reproducible Method to Affect Muscle Development and Growth

Published on: September 20, 2021

High Throughput Assay to Examine Egg-Laying Preferences of Individual Drosophila melanogaster

High Throughput Assay to Examine Egg-Laying Preferences of Individual Drosophila melanogaster

Published on: March 24, 2016

Related Experiment Videos

Last Updated: May 8, 2026

Probing the Limits of Egg Recognition Using Egg Rejection Experiments Along Phenotypic Gradients

Probing the Limits of Egg Recognition Using Egg Rejection Experiments Along Phenotypic Gradients

Published on: August 22, 2018

In Ovo Feeding of Commercial Broiler Eggs: An Accurate and Reproducible Method to Affect Muscle Development and Growth

In Ovo Feeding of Commercial Broiler Eggs: An Accurate and Reproducible Method to Affect Muscle Development and Growth

Published on: September 20, 2021

High Throughput Assay to Examine Egg-Laying Preferences of Individual Drosophila melanogaster

High Throughput Assay to Examine Egg-Laying Preferences of Individual Drosophila melanogaster

Published on: March 24, 2016

Area of Science:

Experimental Design
Statistical Analysis
Animal Science

Background:

Experimental data analysis must align with the actual experimental design.
Standard factorial designs assume independent observations, which is violated in repeated measures designs.
Covariates can influence experimental responses and necessitate analytical adjustments.

Purpose of the Study:

To illustrate the impact of covariates on experimental responses in factorial designs.
To explain the analytical differences between factorial and repeated measures designs.
To demonstrate merging these concepts and adjusting repeated measures analyses for covariates.

Main Methods:

Tutorial-style illustration of covariate effects in factorial designs.
Discussion of analysis differences between factorial and repeated measures designs.
Application of adjusted repeated measures analysis to egg production data with a temperature covariate.

Main Results:

Covariates significantly affect recorded responses in experimental designs.
Repeated measures designs require specific analytical approaches compared to standard factorial designs.
Adjusted analysis for repeated measures data with covariates provides more accurate results.

Conclusions:

Accurate experimental data analysis hinges on appropriate statistical methods tailored to the design.
Covariate adjustment is crucial for valid interpretation of results, especially in repeated measures studies.
The presented methods offer a framework for analyzing complex experimental data, exemplified by poultry egg production.