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

Overview of Biostatistics in Health Sciences01:19

Overview of Biostatistics in Health Sciences

4.5K
Biostatistics involves the application of statistical techniques to scientific research in health-related fields, including biology and public health. These techniques are essential for designing studies, collecting data, and analyzing it to draw meaningful conclusions. Given the complexity of biological processes, particularly in studies involving human subjects, biostatistical methods are crucial for effectively organizing and interpreting data that might otherwise obscure underlying patterns...
4.5K
Biostatistics: Overview01:20

Biostatistics: Overview

696
Biostatistics plays a crucial role in understanding and analyzing data in healthcare and biology. Biostatisticians conduct experiments, gather evidence, and draw meaningful conclusions using statistical methods and techniques. Different variables form the foundation of biostatistical analysis, allowing researchers to understand and interpret data effectively. These variables are classified into different types, each serving a specific purpose in statistical analysis.
Discrete variables are...
696
Statistical Software for Data Analysis and Clinical Trials01:12

Statistical Software for Data Analysis and Clinical Trials

1.4K
Statistical software is pivotal in data analysis and clinical trials by providing tools to analyze data, draw conclusions, and make predictions. These software packages range from simple data management applications to complex analytical platforms, supporting various statistical tests, models, and simulation techniques. Their significance lies in their ability to handle vast amounts of data with precision and efficiency, enabling researchers to validate hypotheses, identify trends, and make...
1.4K
Statgraphics01:10

Statgraphics

369
Statgraphics is a comprehensive statistical software suite designed for both basic and advanced data analysis. Originating in 1980 at Princeton University under Dr. Neil W. Polhemus, it was one of the pioneering tools for statistical computing on personal computers, with its public release in 1982 marking an early milestone in data science software. Over the years, it has evolved into a robust platform for data science, offering tools for regression analysis, ANOVA, multivariate statistics,...
369
Steps in Outbreak Investigation01:18

Steps in Outbreak Investigation

468
In the ever-evolving field of public health, statistical analysis serves as a cornerstone for understanding and managing disease outbreaks. By leveraging various statistical tools, health professionals can predict potential outbreaks, analyze ongoing situations, and devise effective responses to mitigate impact. For that to happen, there are a few possible stages of the analysis:
468
Statistical Methods for Analyzing Epidemiological Data01:25

Statistical Methods for Analyzing Epidemiological Data

864
Epidemiological data primarily involves information on specific populations' occurrence, distribution, and determinants of health and diseases. This data is crucial for understanding disease patterns and impacts, aiding public health decision-making and disease prevention strategies. The analysis of epidemiological data employs various statistical methods to interpret health-related data effectively. Here are some commonly used methods:
864

You might also read

Related Articles

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

Sort by
Same author

A Lasting Legacy: Long-Term Effects of Exercise Training on Cardiometabolic Health in the STRRIDE-Prediabetes Reunion Study.

medRxiv : the preprint server for health sciences·2026
Same author

A Reproducible Pipeline for Processing Commercial Wearable Step-Count Data in Aging Cohorts: Application and Evaluation in the STRRIDE-PD Reunion Study.

medRxiv : the preprint server for health sciences·2026
Same author

Workplace Productivity Loss in Patients with Progressive Pulmonary Fibrosis: Data from the ILD-PRO Registry.

Lung·2026
Same author

AI-induced never-skilling in medical education.

Nature medicine·2026
Same author

The detectability paradox: bilingual medical report generation with open-weight models and the limits of human oversight.

Journal of the American Medical Informatics Association : JAMIA·2026
Same author

SpNeigh: spatial neighborhood and differential expression analysis for high-resolution spatial transcriptomics.

NAR genomics and bioinformatics·2026
Same journal

A Repeated Block Perturbation Subsampling for Large-Scale Longitudinal Data.

Journal of statistical theory and practice·2026
Same journal

Estimating Baseline Survival Function in the Proportional Hazards Model Under Monotone Hazards.

Journal of statistical theory and practice·2026
Same journal

A Statistical Analysis Plan Template for Observational Studies: Promoting Quality and Rigor in Research.

Journal of statistical theory and practice·2025
Same journal

More than presence-absence; modelling (e)DNA concentration across time and space from qPCR survey data.

Journal of statistical theory and practice·2025
Same journal

A Weighted Survival Regression Framework for Incorporating External Prediction Information.

Journal of statistical theory and practice·2025
Same journal

Optimal Designs for Discrete Choice Models Via Graph Laplacians.

Journal of statistical theory and practice·2025
See all related articles

Related Experiment Video

Updated: Jan 8, 2026

Facilitating the Analysis of Immunological Data with Visual Analytic Techniques
10:58

Facilitating the Analysis of Immunological Data with Visual Analytic Techniques

Published on: January 2, 2011

10.5K

Enhancing Team Science by Training Collaborative Biostatisticians to have a Strong Statistical Voice.

Gina-Maria Pomann1, Steven C Grambow1, Marissa C Ashner1

  • 1Department of Biostatistics and Bioinformatics, Duke University School of Medicine, Durham, NC USA.

Journal of Statistical Theory and Practice
|December 18, 2025
PubMed
Summary
This summary is machine-generated.

New biostatisticians need training in strong statistical voice to ensure ethical practices and collaboration. Online videos offer a scalable solution, with positive initial feedback for improving teamwork in biomedical research.

Keywords:
Professional developmentStatistical competenciesStrong statistical voiceTeam science trainingWorkforce development

More Related Videos

Author Spotlight: Advancing Prostate Cancer Research Through Improved Tissue Sampling and Biobanking
07:34

Author Spotlight: Advancing Prostate Cancer Research Through Improved Tissue Sampling and Biobanking

Published on: November 17, 2023

1.1K
A Quantitative Fitness Analysis Workflow
11:39

A Quantitative Fitness Analysis Workflow

Published on: August 13, 2012

14.9K

Related Experiment Videos

Last Updated: Jan 8, 2026

Facilitating the Analysis of Immunological Data with Visual Analytic Techniques
10:58

Facilitating the Analysis of Immunological Data with Visual Analytic Techniques

Published on: January 2, 2011

10.5K
Author Spotlight: Advancing Prostate Cancer Research Through Improved Tissue Sampling and Biobanking
07:34

Author Spotlight: Advancing Prostate Cancer Research Through Improved Tissue Sampling and Biobanking

Published on: November 17, 2023

1.1K
A Quantitative Fitness Analysis Workflow
11:39

A Quantitative Fitness Analysis Workflow

Published on: August 13, 2012

14.9K

Area of Science:

  • Biostatistics
  • Biomedical Research
  • Scientific Collaboration

Background:

  • Strong statistical voice is essential for biostatisticians in biomedical research teams.
  • This skill involves advocating for ethical statistical practices and resolving scientific differences.
  • New graduates often lack formal training in developing a strong statistical voice.

Purpose of the Study:

  • To present a scalable training approach for developing statistical voice in biostatisticians.
  • To create online video didactic materials for this purpose.
  • To evaluate the effectiveness of these materials through a user survey.

Main Methods:

  • Development of online video modules covering manuscript review and study design discussions.
  • Conducting a survey among biostatistics staff at Duke University's BERD Core.
  • Analyzing survey responses regarding the importance and clarity of training materials.

Main Results:

  • All survey respondents affirmed the critical importance of statistical voice in practice.
  • The clarity of training materials and examples was positively received.
  • Suggestions for improvement included increased video engagement and hands-on exercises.

Conclusions:

  • Online videos provide a viable, scalable method for training biostatisticians in statistical voice.
  • Further development should incorporate user feedback to enhance engagement and practical application.
  • This training is vital for fostering effective interdisciplinary collaboration in biomedical research.