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....

Dec 17, 2017

Excellent course that is jam-packed with useful material! It is quite challenging and gives a thorough grounding in how to approach the process of selecting a linear regression model for a data set.

Feb 01, 2017

It really helped me to have a better understanding of these Regression Models. However, I've noticed that there is a video recording repeated: Week 3, Model Selection. Part 3 is included in Part 2.

필터링 기준:

교육 기관: Izabela E

•Aug 12, 2016

Difficult, fast peaced and not well explained. Requires a lot of work.

교육 기관: Ritu B

•Feb 07, 2016

Appears more like a revision for those who already know the content than geared towards those new to the subject.

교육 기관: Coral P

•Jul 20, 2017

I would like to propose that instead of putting the optional reading materials at the back, it should be put up front and mandatory. Else we can't follow the videos

교육 기관: Mohamed A

•Nov 02, 2016

This course failed greatly to balance the workload by week. The third week which I think was the most important one have too many information to learn and assimilate whereas the first two weeks could be rearranged to start multivariate regression earlier. Another proof of week 3 issue: the related swirl exercises start in week2 (2 of them) and finish in week4 (2 more exercises) !!!!!

I think one of the most important expertise and knowledge that a data scientist must know and master was unfairly squeezed in one week leaving no time for the learner/student to do more search/exercises on the subject.

교육 기관: Pedro J

•Jun 06, 2016

The professor doesn't explain clearly as part of the videos is his correcting himself or saying the same thing two or three times. And why must the videos show the teacher? It distracts from the slides and seeing him move doesn't help understand anything better

Concepts like VIF or hat values are not very well explained by the teacher, at least the SWIRL lesson explains it correctly. ANOVA and ANCOVA are mentioned in the description but they aren't explained anywhere. ANOVA is used without any explanation of what it is.

I found myself searching online for other sources to understand the concepts.

교육 기관: Daniel R

•May 14, 2016

Some topics that are important, are obviated

교육 기관: Stefano G

•Jul 20, 2017

I love the content but:

imprecision (a lot),

lack of explanation

...

for one of the most difficult subject in the specialization.

Last commit/update for the video from the teacher 1/2 year ago: are the materials update?

교육 기관: Paul K

•Mar 28, 2017

Slightly better than the Statistical Inference course, but many of the same technical and delivery defects persist. With an otherwise high quality program, I recommend re-producing the inference and regression lectures to increase the overall value of the curriculum.

교육 기관: Benjamin S

•Jan 12, 2018

Material is too dense for the time spent engaged in class. Difficult to stay engaged with lectures, which spend a lot of time on the underlying mathematical concepts. The conceptual underpinnings are very important, but due to the limited timeframe available to present the material, the application of the concepts was done quickly, almost as an aside. The bridges from concept to practical application are very weak.

교육 기관: Grigory S

•Aug 20, 2018

One of the most difficult courses in the whole programme. From my point of view it is very important, but not so well explained. I had to go through other training sessions in order to understand the concept based on numerous practical examples and then return to Coursera to finish it up.

교육 기관: Ankit S

•Oct 24, 2018

not effective for new learnners

교육 기관: Thej K R

•May 13, 2019

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!

교육 기관: Shahryar N

•Nov 29, 2018

The course is awfully simplified.

교육 기관: Tom

•Jul 22, 2017

Terrible. If you want to learn about regression, even in R, go elsewhere. This course damages the brands of Johns Hopkins and Coursera...anybody heard of quality control?

교육 기관: Matt G

•Feb 15, 2016

Poorly designed, executed and instructed. Too much is left off the materials.

교육 기관: Stephen E

•Jun 27, 2016

To be honest I don't think this is worth the money.

교육 기관: Derek P

•Aug 18, 2016

The course is essentially just a review of formulas with very little intuition explained to the beginner. It was necessary to use a collection of outside material from other courses and readings to learn the concepts. This course needs to be completely redone with a focus on developing a student's intuition for the material and then support this intuition with basic examples that build as the course progresses. A fundamental demonstration of how to use R to work through regression models (starting from square one) should be added so that this becomes a self-contained course. As it currently stands it is a collection of poorly integrated slides and concepts that serve to confuse the student more than educate. Other classes teach this material infinitely better.

교육 기관: Fabiana G

•Aug 31, 2016

I was really disappointed with this course. I took the other courses from Brian Caffo and truly enjoyed them. For the previous courses, I've always used the books and they helped me tremendously to be able to comprehend the material. There is a book for Regression Models but but it's a real mess. It feels like a draft that no one cared to take a second look. There is a bunch of wrong code and typos. The explanation doesn't go as far as it should. I had to resort to many different sources just to be able to get by the course. I hope the instructors review this course soon because it does not have the same quality as others. If they don't review it, don't bother paying for it. Try learning Regression Models elsewhere.

교육 기관: Vineet J

•Jul 30, 2017

not good tutor

교육 기관: louis d

•Jun 11, 2016

Content and quizz are not aligned.

Mentors answer to 0% of the forum posts.

Poor student community.

Do not pay for this course, just follow the swirl and/or get some tuto about regressions.

교육 기관: Martin L

•Jul 26, 2017

Very poor - the worst of the specialization courses by far. The lectures are confusing and poorly presented. If you want to understand regression you'll have to look elsewhere.

교육 기관: Eric T

•Feb 21, 2017

Important material, poorly taught.

교육 기관: Robert O

•Apr 06, 2016

Very little depth. I don't recommend this if you don't already have background in statistics or R. I really didn't learn anything. I mostly just gamed the quizzes and projects.

교육 기관: Satakarni B

•Nov 08, 2016

Not worth it for the bucks.

Instructor has tried his best to make no sense of the subject.

I would be happy for a refund.

교육 기관: Adnan B

•Aug 13, 2019

This is the whole course that kind of discouraged me persuing data science field... i wish i wish i wish there was different instructor