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.
Data Science for Health Research Specialization
Discover new skills with 30% off courses from industry experts. Save now.
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
Instructors: Bhramar Mukherjee
1,693 already enrolled
Included with 
Get in-depth knowledge of a subject
(9 reviews)
Intermediate level
Recommended experience
3 months at 10 hours a week
Flexible schedule
Earn a career credential
Share your expertise with employers
Get in-depth knowledge of a subject
(9 reviews)
Intermediate level
Recommended experience
3 months at 10 hours a week
Flexible schedule
Earn a career credential
Share your expertise with employers
What you'll learn
Skills you'll gain
- Exploratory Data Analysis
- Data Wrangling
- Regression Analysis
- Statistical Modeling
- Statistical Methods
- Classification And Regression Tree (CART)
- Data Visualization Software
- Data Analysis
- Statistical Visualization
- Statistical Analysis
- Statistical Inference
- Probability & Statistics
- Plot (Graphics)
- Scatter Plots
- Data Visualization
- Predictive Analytics
- Tidyverse (R Package)
Tools you'll learn
What’s included
Shareable certificate
Add to your LinkedIn profile
Taught in English
29 practice exercises
Advance your subject-matter expertise
- Learn in-demand skills from university and industry experts
- Master a subject or tool with hands-on projects
- Develop a deep understanding of key concepts
- Earn a career certificate from University of Michigan
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
Skills you'll gain
Category: R Programming
Category: Scatter Plots
Category: Ggplot2
Category: Data Manipulation
Category: Data Wrangling
Category: Tidyverse (R Package)
Category: Histogram
Category: Data Visualization Software
Category: Scripting
Category: Plot (Graphics)
Category: Exploratory Data Analysis
Category: Statistical Visualization
Category: Rmarkdown
Category: Software Installation
Category: Package and Software Management
Category: Data Visualization
Category: Data Import/Export
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: Statistical Modeling
Category: Regression Analysis
Category: Statistical Inference
Category: Statistical Hypothesis Testing
Category: Statistical Analysis
Category: Probability & Statistics
Category: Correlation Analysis
Category: Statistical Methods
Category: Predictive Modeling
Category: Data Analysis
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
Skills you'll gain
Category: Regression Analysis
Category: Statistical Analysis
Category: Statistical Hypothesis Testing
Category: Statistical Inference
Category: R Programming
Category: Statistical Methods
Category: Probability & Statistics
Category: Statistics
Category: Descriptive Statistics
Category: Biostatistics
Category: Data Analysis
Category: Classification And Regression Tree (CART)
Category: Statistical Modeling
Category: Risk Analysis
Category: Predictive Analytics
Earn a career certificate
Add this credential to your LinkedIn profile, resume, or CV. Share it on social media and in your performance review.
Instructors
Offered by
Why people choose Coursera for their career
Felipe M.
Learner since 2018
"To be able to take courses at my own pace and rhythm has been an amazing experience. I can learn whenever it fits my schedule and mood."
Jennifer J.
Learner since 2020
"I directly applied the concepts and skills I learned from my courses to an exciting new project at work."
Larry W.
Learner since 2021
"When I need courses on topics that my university doesn't offer, Coursera is one of the best places to go."
Chaitanya A.
"Learning isn't just about being better at your job: it's so much more than that. Coursera allows me to learn without limits."
Open new doors with Coursera Plus
Unlimited access to 10,000+ world-class courses, hands-on projects, and job-ready certificate programs - all included in your subscription
Advance your career with an online degree
Earn a degree from world-class universities - 100% online
Join over 3,400 global companies that choose Coursera for Business
Upskill your employees to excel in the digital economy
Frequently asked questions
There are three courses in this Specialization. Course 1 is four weeks long, Course 2 and Course 3 are each three weeks long. In total, this specialization has 10 weeks of learning.
There are no formal requirements to take this specialization. It is expected that learners understand data important for public health, have a basic understanding of algebra and probability but they do not need to have any formal statistical training or credentials. Course 1 is primarily directed at those who have no previous experience working with R.
Each course can be completed as a standalone or as part of the three-course specialization. Course 1 is primarily directed at those who have no previous experience working with R. Although it is not required, we encourage you to take all three courses in this specialization.
More questions
Financial aid available,