Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Concept Videos

Regression Analysis01:11

Regression Analysis

Regression analysis is a statistical tool that describes a mathematical relationship between a dependent variable and one or more independent variables.
In regression analysis, a regression equation is determined based on the line of best fit– a line that best fits the data points plotted in a graph. This line is also called the regression line. The algebraic equation for the regression line is called the regression equation. It is represented as:
Microsoft Excel: Regression Analysis01:18

Microsoft Excel: Regression Analysis

Regression analysis in Microsoft Excel is a powerful statistical method for examining the relationship between a dependent variable and one or more independent variables. It's used extensively in fields such as economics, biology, and business to predict outcomes, understand relationships, and make data-driven decisions. The most common type is linear regression, which attempts to fit a straight line through the data points to model the relationship between variables.
To perform regression...
Regression Toward the Mean01:52

Regression Toward the Mean

Regression toward the mean (“RTM”) is a phenomenon in which extremely high or low values—for example, and individual’s blood pressure at a particular moment—appear closer to a group’s average upon remeasuring. Although this statistical peculiarity is the result of random error and chance, it has been problematic across various medical, scientific, financial and psychological applications. In particular, RTM, if not taken into account, can interfere when researchers try to extrapolate results...
Multiple Regression01:25

Multiple Regression

Multiple regression assesses a linear relationship between one response or dependent variable and two or more independent variables. It has many practical applications.
Farmers can use multiple regression to determine the crop yield based on more than one factor, such as water availability, fertilizer, soil properties, etc. Here, the crop yield is the response or dependent variable as it depends on the other independent variables. The analysis requires the construction of a scatter plot...
Residuals and Least-Squares Property01:11

Residuals and Least-Squares Property

The vertical distance between the actual value of y and the estimated value of y. In other words, it measures the vertical distance between the actual data point and the predicted point on the line
If the observed data point lies above the line, the residual is positive, and the line underestimates the actual data value for y. If the observed data point lies below the line, the residual is negative, and the line overestimates the actual data value for y.
The process of fitting the best-fit...
Correlation and Regression00:53

Correlation and Regression

In statistics, correlation describes the degree of association between two variables. In the subfield of linear regression, correlation is mathematically expressed by the correlation coefficient, which describes the strength and direction of the relationship between two variables. The coefficient is symbolically represented by 'r' and ranges from -1 to +1. A positive value indicates a positive correlation where the two variables move in the same direction. A negative value suggests a negative...

You might also read

Related Articles

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

Sort by
Same author

The Effect of Volitional Preemptive Abdominal Contraction on Biomechanical Measures During A Front Versus Back Loaded Barbell Squat.

International journal of sports physical therapy·2023
Same author

The effect of forearm position on elbow flexion strength in nursing, occupational, and physical therapy students.

Work (Reading, Mass.)·2021
Same author

Effect of overground locomotor training on ventilatory kinetics and rate of perceived exertion in persons with cervical motor-incomplete spinal cord injury.

Spinal cord series and cases·2019
Same author

Grip strength of Texas Special Olympians.

Perceptual and motor skills·2006
Same author

Isometric strength and dynamic back extensor endurance are unrelated in children ages 6-10 years: a pilot study.

Perceptual and motor skills·2005
Same author

Mismatch of school desks and chairs by ethnicity and grade level in middle school.

Work (Reading, Mass.)·2002
Same journal

Higher Heart Rates During Locomotor High-Intensity Interval Training Are Associated With Gait Asymmetry and Fatigue After Stroke.

Cardiopulmonary physical therapy journal·2026
Same journal

Reducing Upper Extremity Precautions After Lung Transplant: The Clamshell Protocol Pilot Study.

Cardiopulmonary physical therapy journal·2025
Same journal

Condensed Outpatient Rehabilitation Early After Lung Transplantation: A Retrospective Analysis of 6-Minute Walk Distance and Its Predictors.

Cardiopulmonary physical therapy journal·2025
Same journal

Group Versus Individual Rehabilitation in Lung Transplantation: A Retrospective Noninferiority Assessment.

Cardiopulmonary physical therapy journal·2025
Same journal

Rehabilitation for Physical Frailty in Lung Transplant Candidates: A Systematic Review.

Cardiopulmonary physical therapy journal·2025
Same journal

Shared Medical Appointments to Improve Equitable Access to Rehabilitative Care for Long COVID.

Cardiopulmonary physical therapy journal·2025
See all related articles

Related Experiment Video

Updated: Jun 13, 2026

Eye-tracking to Distinguish Comprehension-based and Oculomotor-based Regressive Eye Movements During Reading
05:54

Eye-tracking to Distinguish Comprehension-based and Oculomotor-based Regressive Eye Movements During Reading

Published on: October 18, 2018

Regression analysis for prediction: understanding the process.

Phillip B Palmer1, Dennis G O'Connell

  • 1Hardin-Simmons University, Department of Physical Therapy, Abilene, TX.

Cardiopulmonary Physical Therapy Journal
|May 15, 2010
PubMed
Summary
This summary is machine-generated.

This study simplifies regression analysis for predicting cardiorespiratory fitness and outcomes. It aims to improve reader comprehension of this common statistical method in research.

More Related Videos

Probing the Limits of Egg Recognition Using Egg Rejection Experiments Along Phenotypic Gradients
07:34

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

Published on: August 22, 2018

Related Experiment Videos

Last Updated: Jun 13, 2026

Eye-tracking to Distinguish Comprehension-based and Oculomotor-based Regressive Eye Movements During Reading
05:54

Eye-tracking to Distinguish Comprehension-based and Oculomotor-based Regressive Eye Movements During Reading

Published on: October 18, 2018

Probing the Limits of Egg Recognition Using Egg Rejection Experiments Along Phenotypic Gradients
07:34

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

Published on: August 22, 2018

Area of Science:

  • Exercise Physiology
  • Biostatistics

Background:

  • Cardiorespiratory fitness research frequently employs regression analysis.
  • Understanding regression analysis is crucial for interpreting study findings on cardiorespiratory status and outcomes.
  • Complex statistical methods can pose a barrier to reader comprehension.

Purpose of the Study:

  • To simplify the application of regression analysis in predicting cardiorespiratory fitness.
  • To enhance reader understanding of statistical methodologies in cardiorespiratory research.
  • To provide accessible explanations and examples of regression analysis.

Main Methods:

  • The study focuses on explaining the principles of regression analysis.
  • Illustrative examples are used to demonstrate the application of regression analysis.
  • The approach aims for clarity and ease of understanding for a broader audience.

Main Results:

  • The simplified approach facilitates a clearer understanding of regression analysis.
  • Readers can more easily grasp the prediction of cardiorespiratory status and outcomes.
  • The use of examples aids in demystifying the statistical technique.

Conclusions:

  • Simplifying regression analysis improves accessibility to cardiorespiratory fitness research.
  • Enhanced understanding of statistical methods can broaden the impact of research findings.
  • This approach supports more effective communication of scientific results.