Linear Regression Modeling for Health Data

This course is part of Data Science for Health Research Specialization

Instructors: Philip S. Boonstra +1 more

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

  •   Statistical Methods
  •   Correlation Analysis
  •   Data Analysis
  •   Statistical Hypothesis Testing
  •   Predictive Modeling
  •   Statistical Analysis
  •   Probability & Statistics
  •   Statistical Inference
  •   Statistical Modeling
  •   Regression Analysis
  • There are 3 modules in this course

    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 first look at the ever-popular t-test and delve further into linear regression. They will also learn how to fit and interpret regression models for a continuous outcome with multiple predictors. All concepts taught in this course will be covered with multiple modalities: slide-based lectures, guided coding practice with the instructor, and independent but structured exercises.

    Simple Linear Regression

    Multiple Linear Regression

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