Data Science for Health Research
Description
In Data Science for Health Research, learn to organize and visualize health data using statistical analysis in programs like R. Explore how to translate data, interpret statistical models, and predict outcomes to help make data-informed decisions within the public health field.
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Subject
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Language
English
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Duration
10 weeks
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Status
Available
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U-M Credit Eligible
No
Data Science
Instructors
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Philip S. Boonstra, PhD
Associate Professor, Biostatistics
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Bhramar Mukherjee PhD
Professor of Epidemiology
Courses (3)
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Learn moreArranging and Visualizing Data in R
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4 weeks
Learn to organize, summarize, and visualize data in R using tools like RStudio, ggplot, and data transformation techniques. -
Learn moreLinear Regression Modeling for Health Data
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3 weeks
Get started with linear regression and learn how to analyze health data using statistical models, coding practice, and guided exercises. -
Learn moreLogistic Regression and Prediction for Health Data
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3 weeks
Explore binary outcomes and build logistic regression models using R to analyze and predict health data with guided coding practice.