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
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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Arranging and Visualizing Data in R (Cuorsera)

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 its companion, RStudio. Then, they will read data into the R environment and prepare it for summary and analysis. A wide [...]

Logistic Regression and Prediction for Health Data (Coursera)

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 more broadly using logistic regression. They will understand the connection between prevalence, risk ratios, and odds ratios. By the end of this course, learners [...]

Linear Regression Modeling for Health Data (Coursera)

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' and introduces learners to the core ideas of traditional statistical inference and reasoning. Learners will get their [...]