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

4.7K
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...
4.7K
Biostatistics: Overview01:20

Biostatistics: Overview

732
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...
732
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
Introduction to R01:11

Introduction to R

4.3K
R is a powerful software environment for statistical computing and graphics. Originating as an implementation of the S language, developed at Bell Laboratories, R has evolved into a robust, open-source statistical software favored by statisticians and data scientists worldwide. Its comprehensive suite includes data manipulation, calculation, and graphical display capabilities, making it versatile for data analysis and visualization. Its programming language is at the core of R's...
4.3K
Steps in Outbreak Investigation01:18

Steps in Outbreak Investigation

492
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:
492
Statistical Methods for Analyzing Epidemiological Data01:25

Statistical Methods for Analyzing Epidemiological Data

898
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:
898

You might also read

Related Articles

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

Sort by
Same author

Metabolic phenotypes of doxorubicin-induced cardiotoxicity among patients with breast cancer.

Metabolomics : Official journal of the Metabolomic Society·2026
Same author

Design and methodology of a randomized clinical trial of prolonged daily antibiotic suppression with and without fulguration for uncomplicated recurrent urinary tract infections in women.

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

Sex differences in the peripheral determinants of oxygen transport and utilization in patients with heart failure with preserved ejection fraction.

American journal of physiology. Heart and circulatory physiology·2026
Same author

Association of Neighborhood Social Vulnerability With Metastatic Cancer at Diagnosis.

Cancer medicine·2026
Same author

Discovery, phylogenetic, and comparative genomic analysis of novel avian gammacoronaviruses identified in feral pigeons (<i>Columba livia domestica</i>).

Journal of virology·2025
Same author

Privy by the Bay: Emerging hotspot analysis of 311 reports of human/animal waste near San Francisco Pit Stop locations, 2009-2022.

PloS one·2025

Related Experiment Video

Updated: Jan 16, 2026

Project-Based Learning Guidelines for Health Sciences Students: An Analysis with Data Mining and Qualitative Techniques
13:44

Project-Based Learning Guidelines for Health Sciences Students: An Analysis with Data Mining and Qualitative Techniques

Published on: December 9, 2022

4.2K

From Exams to Engagement: Evaluating Project-Based Learning in Introductory Biostatistics With R for Public Health

Kevin C Lutz1, Sean G Young1, Lindsey Chambers1

  • 1Peter O'Donnell Jr School of Public Health, The University of Texas Southwestern Medical Center, Dallas, TX, USA.

Journal of Medical Education and Curricular Development
|September 29, 2025
PubMed
Summary
This summary is machine-generated.

Replacing traditional exams with collaborative projects in graduate biostatistics courses improved student performance and engagement. This project-based learning approach enhances R programming skills for public health students.

Keywords:
assessmentsbiostatistics educationprogramming in Rproject-based learningpublic health education

More Related Videos

A User-friendly and Powerful R Analysis of Large-scale Datasets
10:56

A User-friendly and Powerful R Analysis of Large-scale Datasets

Published on: November 4, 2025

339
Improving Student Outcomes with an Adaptable Molecular Cloning Course-Based Undergraduate Research Experience
10:17

Improving Student Outcomes with an Adaptable Molecular Cloning Course-Based Undergraduate Research Experience

Published on: November 15, 2024

1.6K

Related Experiment Videos

Last Updated: Jan 16, 2026

Project-Based Learning Guidelines for Health Sciences Students: An Analysis with Data Mining and Qualitative Techniques
13:44

Project-Based Learning Guidelines for Health Sciences Students: An Analysis with Data Mining and Qualitative Techniques

Published on: December 9, 2022

4.2K
A User-friendly and Powerful R Analysis of Large-scale Datasets
10:56

A User-friendly and Powerful R Analysis of Large-scale Datasets

Published on: November 4, 2025

339
Improving Student Outcomes with an Adaptable Molecular Cloning Course-Based Undergraduate Research Experience
10:17

Improving Student Outcomes with an Adaptable Molecular Cloning Course-Based Undergraduate Research Experience

Published on: November 15, 2024

1.6K

Area of Science:

  • Public Health Education
  • Biostatistics Pedagogy
  • Educational Technology

Background:

  • Traditional assessments in graduate biostatistics courses may not fully capture student learning or engagement.
  • There is a need for innovative teaching methods to enhance practical data analysis skills using R programming.

Purpose of the Study:

  • To evaluate the impact of replacing a traditional midterm exam with a collaborative project-based assessment on student performance and engagement.
  • To assess student satisfaction and confidence in R programming and data analysis skills.

Main Methods:

  • A retrospective study compared two semesters of an introductory graduate biostatistics course.
  • One cohort (Fall 2023) had traditional exams; the other (Fall 2024) replaced the midterm with a project-based assessment.
  • Student performance, course grades, and post-project survey data were analyzed.

Main Results:

  • The project-based cohort demonstrated significantly higher and more consistent midterm and final exam scores.
  • Overall course grades were higher, and students reported increased satisfaction, confidence in R, and appreciation for real-world applications.
  • Challenges included group dynamics and time management.

Conclusions:

  • Collaborative project-based assessments significantly enhance student performance, engagement, and satisfaction in biostatistics.
  • Project-based learning is a valuable strategy for public health education, fostering applied data analysis skills with R.