Biostatistical Methods I: Linear Regression and ANOVA

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.
 
Course typically offered: Online in Fall and Spring

Prerequisites: Biostatistics and SAS Programming I or equivalent experience required.

Next Steps: Upon completion of this course, consider taking Biostatistical Methods II to continue learning.