Multivariable Regression part I

Loading...
Johns Hopkins University
4.4 (2,675 ratings) | 83K Students Enrolled
Course 7 of 10 in the Data Science Specialization
View Syllabus

Skills You'll Learn

Model Selection, Generalized Linear Model, Linear Regression, Regression Analysis

Reviews

4.4 (2,675 ratings)
  • 5 stars
    1,669 ratings
  • 4 stars
    653 ratings
  • 3 stars
    216 ratings
  • 2 stars
    82 ratings
  • 1 star
    55 ratings
CS

Mar 11, 2019

This module was the maximum. I learned how powerful the use of Regression Models techniques in Data Science analysis is. I thank Professor Brian Caffo for sharing his knowledge with us. Thank you!

AC

Aug 11, 2017

Regression analysis is something that is kind of easy for people to understand (outcome and predictor - people get that!). It's easy to explain to people. So much practice using the lm function!

From the lesson
Week 3: Multivariable Regression, Residuals, & Diagnostics
This week, we'll build on last week's introduction to multivariable regression with some examples and then cover residuals, diagnostics, variance inflation, and model comparison.

Taught By

  • Brian Caffo, PhD

    Brian Caffo, PhD

    Professor, Biostatistics
  • Roger D. Peng, PhD

    Roger D. Peng, PhD

    Associate Professor, Biostatistics
  • Jeff Leek, PhD

    Jeff Leek, PhD

    Associate Professor, Biostatistics

Explore our Catalog

Join for free and get personalized recommendations, updates and offers.