Logistic Regression in R for Public Health
Master logistic regression analysis using R for public health applications. Learn model building, assessment, and interpretation.
Master logistic regression analysis using R for public health applications. Learn model building, assessment, and interpretation.
This course cannot be purchased separately - to access the complete learning experience, graded assignments, and earn certificates, you'll need to enroll in the full Statistical Analysis with R for Public Health Specialization program. You can audit this specific course for free to explore the content, which includes access to course materials and lectures. This allows you to learn at your own pace without any financial commitment.
4.8
(355 ratings)
13,300 already enrolled
Instructors:
English
پښتو, বাংলা, اردو, 2 more
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What you'll learn
Perform descriptive statistics and create visualizations using R
Run and interpret simple and multiple logistic regression analyses
Evaluate model assumptions and assess model fit
Apply appropriate model selection techniques
Interpret odds ratios and their significance
Handle real-world public health data challenges
Skills you'll gain
This course includes:
2 Hours PreRecorded video
8 quizzes
Access on Mobile, Tablet, Desktop
FullTime access
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There are 4 modules in this course
This comprehensive course focuses on applying logistic regression analysis to public health data using R. Students learn to handle messy real-world datasets, prepare data for analysis, run simple and multiple logistic regression models, and evaluate model fit. The curriculum emphasizes practical applications in public health, covering topics from basic odds ratios to advanced model selection techniques. Special attention is given to interpreting results from both individual and population health perspectives.
Introduction to Logistic Regression
Module 1 · 2 Hours to complete
Logistic Regression in R
Module 2 · 2 Hours to complete
Running Multiple Logistic Regression in R
Module 3 · 2 Hours to complete
Assessing Model Fit
Module 4 · 4 Hours to complete
Fee Structure
Instructor
Expert in Medical Statistics and Healthcare Quality
Prof. Alex Bottle is a Professor in Medical Statistics and co-director of the Dr Foster Unit at Imperial College London. His research is centered on measuring and understanding variations in healthcare quality and safety through the use of large databases. In addition to his research, Prof. Bottle teaches across various undergraduate and postgraduate programs, supervises and examines PhD students in fields such as surgery, cardiovascular risk, and digital health, and provides statistical training to the UK public sector.
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4.8 course rating
355 ratings
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