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
This course provides a first look at the R statistical environment. Beginning with step-by-step instructions on downloading and installing the software, learners will first practice navigating R and i -
Learn moreLinear Regression Modeling for Health Data
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3 weeks
This course provides learners with a first look at the world of statistical modeling. It begins with a high-level overview of different philosophies on the question of 'what is a statistical model' an -
Learn moreLogistic Regression and Prediction for Health Data
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3 weeks
This course introduces learners to the analysis of binary/dichotomous outcomes. Learners will become familiar with fundamental tests for two-group comparisons and statistical inference plus prediction