University of Michigan
Data Science for Health Research Specialization
University of Michigan

Data Science for Health Research Specialization

Wrangle, Visualize and Analyze Health Data. Import, process data and fit basic statistical models to analyze health outcome data, all in the R statistical environment

Taught in English

Bhramar Mukherjee
Philip S. Boonstra

Instructors: Bhramar Mukherjee

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Specialization - 3 course series

Get in-depth knowledge of a subject

Intermediate level

Recommended experience

3 months at 10 hours a week
Flexible schedule
Learn at your own pace

Specialization - 3 course series

Get in-depth knowledge of a subject

Intermediate level

Recommended experience

3 months at 10 hours a week
Flexible schedule
Learn at your own pace

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Specialization - 3 course series

What you'll learn

  • Become knowledgeable about and conversant in the R environment

  • Format and manipulate data within R into suitable formats

  • Develop an intuition for doing exploratory data analysis

  • Develop a workflow in R

What you'll learn

  • Become knowledgeable about the concept of statistical modeling and the basics of statistical inference

  • Recognize, fit, and interpret a simple linear regression model

  • Develop intuition to fit and interpret a multiple regression model

Skills you'll gain

Category: Implement and interpret two-sample comparison of means
Category: Fit and summarize linear regression with multiple predictors
Category: Conceptualize statistical models

What you'll learn

  • Understand how binary outcomes arise and know the difference between prevalence, risk ratios, and odds ratios

  • Use logistic regression to estimate and interpret the association between one or more predictors and a binary outcome

  • Understand the principles for using logistic regression to make predictions and assessing the quality of those predictions

Instructors

Bhramar Mukherjee
University of Michigan
2 Courses394 learners

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