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Learner Reviews & Feedback for Regression Models by Johns Hopkins University

4.4
stars
3,225 ratings
549 reviews

About the Course

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....

Top reviews

KA
Dec 16, 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.

BA
Jan 31, 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.

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451 - 475 of 529 Reviews for Regression Models

By VenusW

Jan 9, 2017

This course is great, instructor is good, however, the material of this course is not well organized, even the swirl practice is not put in the correct week, not in the same pace as the lectures. The quiz and project are far much easier than lecture content.

By Brandon K

Mar 30, 2016

I found the videos tough to watch. I was hoping for something that would be more practical for non-statisticians, but the lectures mainly devolved into mathematical proofs. That said, I did learn some from this class. Just not as much as I'd hoped.

By Zach

Feb 4, 2016

There's just something about the course content that is difficult to attain. It's presented at way too high of a level without enough tangible examples of getting down into the weeds of how to actually perform and interpret the models and functions.

By 장진욱

Feb 14, 2016

The flows of courses instructed by Caffo(Statistical Inference and Regression Models) are too long to concentrate it and the quiz is ​not quite related in lecture.

However, Contents of the book is really good, as well as homework in the book.

By Sarah R

Mar 20, 2016

The instructor is at time incomprehensible. It would be helpful to speak more slowly and pause more often. Otherwise he sounds like repeating something that he's so well memorized after many years of teaching.

By Ramesh G

Jun 4, 2020

Good introduction to linear regression models but fell awfully short on diving a little deep into GLMs and going through use cases to convey how models are built, evaluated and updated in a systemic manner.

By Fulvio B

Apr 27, 2020

The course is interesting but probably overambitious. I think that if you do not have previous experience, with the material provided, it would be hard to have a real understanding of the topics covered.

By Pepijn d G

May 23, 2016

The course is good. Unlike the previous courses I took in this track, there was almost no interaction in the forums and also no-one to give feedback. I wonder if there were any TA's present in this run.

By Raul M

Jan 16, 2019

This course should be targeted for Data Scientists, in my opinion it is more for statisticians.

Too much about the insight of statistics and some but not enough about how to use the statistic tools.

By benjamin s

Jun 20, 2018

A good (although slightly frustrating) course, attempted once but had to come back after studying the material in class, quite a heavy course if you've not been taught regression before

By Guilherme B D J

Aug 21, 2016

Given the importance of this subject, this course should have been split in two or more or have a longer duration to properly address subjects as GLM or model selection techniques.

By Marco A M A

May 9, 2016

This course is better than Statistical Inference, and I think it is as useful. Non credit excersise are still very good at helping with understanding in practice what is going on.

By Rok B

Jun 28, 2019

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

By Jesse K

Nov 2, 2018

The material was a little disjointed and not always explained with examples. Passing this course required a significant amount of outside study and research.

By Jason M C

Mar 29, 2016

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.

By Anamaria A

Mar 12, 2017

Lots of material needs additional study (from different sources) as it's only summarily explained. Much math without the link to the praxis :-(

By Manuel M M

Feb 10, 2020

The content was exposed in a very confused manner. I did not like how the teacher explained. It seemed more difficult than it really is

By LU Z

Sep 26, 2018

Starting from the first week swirl practice, course content is poorly organized making even simple concept difficult to understand.

By Hendrik F

Jan 17, 2016

I find it very tough to understand everything. Buying the course book helps to overcome this. You have to dedicate a lot of time.

By Mark S

Apr 24, 2018

Lots of math, but it would be more productive to focus more on the output of R and better understand the results

By Mertz

Mar 20, 2018

Bad audio and video quality. Too fast on some complex ideas and too slow when come repetitions between videos...

By Andres C S

Mar 1, 2016

I think this course needs more emphasis on practical applications and less mathematical background.

By Erwin V

Dec 20, 2016

Very interesting course, yet course content could be spread more evenly (week 4 is really a lot)

By Prabeeti B

Sep 17, 2019

Course has more theoretical concept than application.. It has to be more application based

By Praveen J

Apr 22, 2020

I think a revamping of the concepts in a more ellabroate way is required in the course