Biostatistical Methods I: Linear Regression and ANOVA
BIOL-40315
This course is designed to provide a solid foundation in regression analysis and ANOVA, with a special focus on applications in the biomedical field. Whether you’re looking to enhance your research skills or apply statistical techniques in your profession, this course will equip you with the knowledge and tools you need.
Course Highlights:
· Comprehensive Coverage: Dive deep into simple and multiple linear regression, analysis of variance (ANOVA), and analysis of covariance (ANCOVA).
· Real-World Applications: Apply what you learn to real-world biomedical data, enhancing your ability to analyze continuous response data effectively.
· Model Building Mastery: Learn various model-building techniques, identify confounders and effect modifiers, and develop strategies for constructing and refining statistical models.
· Model Diagnostics: Understand how to evaluate model fit, address violations of model assumptions, and ensure your analyses are robust and reliable.
· Practical Skills: Gain hands-on experience with R, the leading programming language for statistical analysis, and develop your ability to write clear and concise method and result sections for scientific papers.
· Weekly Practice: Enhance your understanding with weekly practice problems and quizzes, reinforcing key concepts and techniques.
Topics Include:
· Simple and Multiple Linear Regression
· Analysis of Variance (ANOVA) and Covariance (ANCOVA)
· Correlation Analysis
· Model Building Techniques
· Model Diagnostics and Assumption Checking
Why Attend?
By the end of this course, you'll be able to confidently apply regression analysis and ANOVA techniques to your research or professional projects. You'll develop a keen understanding of how to build, evaluate, and refine statistical models, making you a valuable asset in any data-driven environment.
Next Steps: Upon completion of this course, consider taking Biostatistical Methods II to continue learning.
Course Information
Course sessions
Section ID:
Class type:
This course is entirely web-based and to be completed asynchronously between the published course start and end dates. Synchronous attendance is NOT required.
You will have access to your online course on the published start date OR 1 business day after your enrollment is confirmed if you enroll on or after the published start date.
Textbooks:
No textbook required.
Policies:
- No refunds after: 4/15/2025
Schedule:
Instructor: Arthur Li, M.S.
Biostatistician, City of Hope; Instructor, Department of Preventative Medicine, USC
Arthur Li holds an M.S. in Biostatistics from the University of Southern California. Currently, he is a biostatistician at the City of Hope National Medical Center. Li developed and taught an introductory SAS course at USC for the past six years, and teaches a clinical biostatistics sourse at UC San Diego Extension. In addition to teaching and working on cancer-related research, Li wrote a book titled “Handbook of SAS® DATA Step Programming” which was released in April 2013.
Section ID:
Class type:
This course is entirely web-based and to be completed asynchronously between the published course start and end dates. Synchronous attendance is NOT required.
You will have access to your online course on the published start date OR 1 business day after your enrollment is confirmed if you enroll on or after the published start date.
Textbooks:
All course materials are included unless otherwise stated.
Policies:
- No refunds after: 10/7/2025
Schedule:
Instructor: Arthur Li, M.S.
Biostatistician, City of Hope; Instructor, Department of Preventative Medicine, USC
Arthur Li holds an M.S. in Biostatistics from the University of Southern California. Currently, he is a biostatistician at the City of Hope National Medical Center. Li developed and taught an introductory SAS course at USC for the past six years, and teaches a clinical biostatistics sourse at UC San Diego Extension. In addition to teaching and working on cancer-related research, Li wrote a book titled “Handbook of SAS® DATA Step Programming” which was released in April 2013.
