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. The mission of The Johns Hopkins University is to educate its students and cultivate their capacity for life–long learning, to foster independent and original research, and to bring the benefits of discovery to the world.
Instructor Details
Courses : 7
Specification: Regression Models

51 reviews for Regression Models
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Seyedeh M M –
Awesome class! Highly recommended.
Manny R –
Really Fun Course. There is a lot to learn in this topic and this could be studied for a lifetime. I feel like I could apply this to discover solutions for issues at work.
Yadder A G –
The course was incredible. You can learn a lot of skills about regression models and even more. It would be incredible if the course could have more examples or little excercises.
Dora M –
Good class.
Satish V –
The instructor’s delivery and content, although very professorial was very dry. For students who don’t have that much of a background in regression and statistical inference, I think it would be good to get to the gist/summary – i.e the what (what kind of problem we are trying to solve) and the how (how to do it in R and more importantly how to interpret the results).
John D M –
Overall an excellent course, but there were some issues with the wrong function being specified in one quiz (Q3q6) and the wrong answer in another. Apparently it has been that way for years, according to the forum. The quality of the lectures was very high and the information interesting, so compliments to Dr. Brian Caffo on that. However, the estimated time for completion of each week is ridiculously short compared to reality. Five hours? For me it was more like 20 hours, and more if I did all the Swirl exercises. Such low–balling on the time estimates is typical of the Data Science stream. The final project is given as 2 hours but it was closer to 15 for me. i wish Coursera would go back to the stream model where you could bump yourself to the next intake. That is much less stressful for busy working people like me.
Rodrigo O –
great
MEKIE Y R K –
Really interesting and full of advices. But would like to dig more into the Logistic and poisson regression residuals explanations 🙂
Diego C –
Very good course. Though basic, it provides you with the first tools and knowledge. The forums aren’t what they used to be it seems, but you can find almost any answer there from past courses.
Ekaterina S –
It was a very usefull course. It is a very good approach to the theme – the main essence without much math difficulty.
Thej K R –
Worst teaching by Brian Caffo! typos in quizes after 4 years even. And brian has put very littel effort into making it digestable for students. Look at his lectures on youtube and I have commented at each lecture! So bad. A simple googling outside of his notes was so much more better for understanding regression!
Andrew –
Great introduction to regression models. A ton packed into the class. Be ready to be challenged, but you’ll learn a lot.
YANAN D –
Really Helpful
Nino P –
Similarly to statistical inference, this is a bit harder course in the specialization. Still passable and recommendable.
Alan G B –
It is an excellent initial approach to Regression Models. I was able to apply some of the models in my work. Further analysis of the mathematical and statistical theory is highly recommended.
Ravi K –
This is really a nice training
Jorge B S –
I have loved this introductory course about Regression. The swirl exercises are especially useful to revise the course content and apply the theory.
Sandesh –
For the content covered, I think the course does a good job exposing students to fundamental concepts while also highlighting how much more there is to research in order to gain a solid understanding of this subject matter. The course offers a good foundation, and I hope they come out with a more advanced version of this course for more guided exposure.
Rok B –
Useful class, but the content often simple in nature was explained in a confusing/complicated way. But the material is important and there is purchase for taking the class
Manuel E –
Hard class, documentation could be better, but good content.
Xiaole Z –
helpful!
Siying R –
The lecture is pretty dry to me who had limited vocabulary in the field. It made me went out to find other easier lectures to help me understand. The lecture focus on explaining the basic concept of Regression Models and spend a big chunk of time to explain how the function works. I would prefer to have more time explaining what the numbers mean for the data. The questions in the quiz require us to understand the meaning of the data, so we know what function and number to apply. Maybe it is just me, finding it very challenging to see the connection between the lecture and the quiz.
Alimohammad P –
Very informative course!
Adnan B –
This is the whole course that kind of discouraged me persuing data science field… i wish i wish i wish there was different instructor
Charbel L –
Very comprehensive introduction to regression models. Well done!
Yiyang Z –
Very informative, but could be more interesting and concise.
Naveen S –
really it is very good
Rizwan M –
excellent courseware with assignments
Connor B –
Learned a lot and enjoyed the course project. Would like to have two course projects because I gain the most out of them.
Muhammad Z H –
learning alot
Prabeeti B –
Course has more theoretical concept than application.. It has to be more application based
Will J –
Pros: The instructors of this course are absolutely knowledgable on the content here. The content itself is challenging and applicable to real–world data science challenges. Using R makes this a good course for today’s (2019) current programming world as many professional statisticians will use this language day–to–day. Cons: The content feels mismanaged. Sometimes the Lectures don’t prep you for the practice assignments, and sometimes neither of those prep you for the quizzes particularly well. I had also hoped for some more engaging video content from a course this expensive. Having a professor in his office hastily work through material while there are police sirens outside isn’t exactly pro–level instruction (It is in Baltimore, so I get it). Overall, it’s worth it if you’ve got the time to power through relatively dull lectures. The R based practice assignments are wonderful and the final project incorporates things together nicely.
BOUZENNOUNE Z E –
This was great. However, to follow it more precisely, you need the following: Read the book of linear regression from the same teacher. Usually a useful strategy would be to read each chapter first from the book, then watch the video associated to it, and finally do the swirl exercice. You may need to follow the course notes of this class, they are published in github, and they can help a lot, especially for the quizzes.
Koen V –
The explanation of the right answers from the quiz were quite handy!
Ashwin V –
great course
Dr. T A –
A good review of regression that allows the student to apply practical implementations in R Studio
Channaveer P –
Amazing course… good learning experience. Very useful for my role in my Organization.
Giovanni G –
Very interesting
Manpreet S –
Good Course for beggining
Boris K –
Along with the Statistical Inference Class and Building Predictive Models Class this is one of the best in this Specialization. It is reasonably tough, well–taught, overall great.
Purificacion V –
Es un gran curso para aprender, junto con el resto de los cursos de la especializacion.
gerson d o –
Wonderful!!!!
Luiz E B J –
The content is to long, maybe would be interesting split the content in other modules.
Charles W –
If this was an on–campus course, I would have been a little worried about the quiz grades on the 1st try. However, with the ability to re–take this quizzes, I think this was an Excellent and well thought–out course.
Marcela Q –
Terrible professor, good book
Govind N –
I learnt regression models from this course.
Pedro M –
Great course!
Amanyiraho R –
Gives you the best understanding of the roots of regression models
udaya k b –
neatly placed topics.
Johnnery A –
Excellent!
Rui W –
Awesome Course Content!