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Johns Hopkins University

Regression Models

Johns Hopkins University via Coursera


Linear models, as their name implies, relates an outcome to a set of predictors of interest using linear assumptions. Regression models, a subset of linear models, are the most important statistical analysis tool in a data scientist’s toolkit. This course covers regression analysis, least squares and inference using regression models. Special cases of the regression model, ANOVA and ANCOVA will be covered as well. Analysis of residuals and variability will be investigated. The course will cover modern thinking on model selection and novel uses of regression models including scatterplot smoothing.


  • Week 1: Least Squares and Linear Regression
    • This week, we focus on least squares and linear regression.
  • Week 2: Linear Regression & Multivariable Regression
    • This week, we will work through the remainder of linear regression and then turn to the first part of multivariable regression.
  • 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.
  • Week 4: Logistic Regression and Poisson Regression
    • This week, we will work on generalized linear models, including binary outcomes and Poisson regression.

Taught by

Brian Caffo


2.7 rating, based on 33 Class Central reviews

4.4 rating at Coursera based on 3331 ratings

Start your review of Regression Models

  • Profile image for Esteban López
    Esteban López

    Esteban López completed this course.

    As another one said before, I also survived mr. Caffo's courses. He probably is a good researcher and very intelligent man. But SUCKS as a teacher. Dropped the first time and retake it after using other books as sources, then I passed with 100%. Th…
  • Robert Grutza

    Robert Grutza is taking this course right now, spending 3 hours a week on it and found the course difficulty to be hard.

    I took this class a couple times hoping there would be some improvement in the presentation and materials. There was not. If you have some understanding of linear regression going in you run the risk of unlearning what you previously understood. Who knew this was possible . They need to completely redo this class.
  • Steve Sinai

    Steve Sinai completed this course, spending 10 hours a week on it and found the course difficulty to be hard.

    I took this class last year and don't know if it's changed. I hope so. It tries to cover too much ground given it's only one month long. Another problem was the instructor, Brian Caffo, who seems like a good guy and good researcher, but not an effe…
  • Anonymous

    Anonymous completed this course.

    I agree with a comment above - this class should ideally be completely redone (with a different instructor). The emphasis is on derivation of formulas and techniques, not applications to the real world. Also, the course "textbook" is significantly i…
  • Mark Kaghazgarian is taking this course right now.

    I've struggled a lot to figure out what are the points of the topics which are explaining in this course but actually it wasn't any relation between them neither any practical usage. Despite I've learned so many statistics stuffs by having another…
  • Brandt Pence

    Brandt Pence completed this course, spending 3 hours a week on it and found the course difficulty to be easy.

    Regression Models is the seventh course in the Data Science specialization. As with Statistical Inference, it is taught by Brian Caffo and suffers from the same issues as the preceding course. The course covers least squares, simple linear regressio…
  • Anonymous
    This course gave a thorough explanations of how regression models works. The instructor repeated some basic and difficult points again and again. R ggplot2 was used to visualize the models and residuals etc. There is a swirl() R package to help students understand the course deeply. If you have some mathematical background, try this course first. It will give you solid foundations of linear regression models. If you look for how to apply linear regression models in realities, this course will be a little difficult to start, but will reward finally.
  • Anonymous

    Anonymous completed this course.

    The lectures are completely worthless and don't tell you what you should look at. Instead, its mathematical formulas with statements like:

    "If you run his r statement..."

    (5 lines of code with 10 lines of output...

    "you can see that these are the covariants to use."

    No, I didn't see it. You spent 90% of your time explaining random subtleties of a mathematical equation instead of telling us anything to do with the R code. Heck, anything to do with the material on a high level.

    The material is not that hard (if you learn from other sources), but the course here does nothing to explain it to you.

  • Profile image for Vidit Agarwal
    Vidit Agarwal

    Vidit Agarwal completed this course, spending 14 hours a week on it and found the course difficulty to be hard.

    with all due respect to personal accomplishments of instructure, he completely fails as a teacher.
    Sometimes it became so difficult to figure out where he is leading the course to.. half-baked background explanations are suddenly followed by burst of R codes, rushed through examples and not relatable quiz questions at times. the course quality went all the way downhill as it progressed. I am ending this course more confused now
  • Profile image for Apronin

    Apronin completed this course.

    Horrible presentation of the material! The instructor is clearly delusional -- he has no idea what it means to teach a class. Don't take! Learn this material from other sources.
  • Jason Michael Cherry completed this course, spending 3 hours a week on it and found the course difficulty to be medium.

    This is a decent class, covering linear regression and a few of its variants in good detail. It's a challenging subject, but presented acceptably here.
  • Ani Setchi is taking this course right now.

  • Rafael Prados

    Rafael Prados completed this course.

  • Profile image for Jevgeni Martjushev
    Jevgeni Martjushev

    Jevgeni Martjushev is taking this course right now.

  • Maciej completed this course, spending 4 hours a week on it and found the course difficulty to be medium.

    Although the lectures were a bit chaotic, the quizzes and the project assignment were perfect for me. TBH, I didn't watch the lectures unless there was something I couldn't solve on my own. The questions are well-thought, insightful and help understand the subject (assuming you really want to get into it). And I always found the right answer in the lectures.

    All in all, this course is not suitable for people who would like to be dragged by the hand, and forced to learn something new.
  • Anonymous

    Anonymous completed this course.

    The new vedios that they have added to the course are really good and I really appreciate the effort put in to improve the course. The book on leanpub is nice , the back exercises at the end of each chapter and the vedio solutions that they have provided for each and every question is awesome and it prepares you well for the quizzes and the project .
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    Karri S completed this course.

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    Radomir Nowacki

    Radomir Nowacki completed this course.

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