Regression Models に戻る

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2,984件の評価

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502件のレビュー

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.

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by 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.

by Lee D

•Sep 30, 2016

I again found many of the lectures to be difficult to follow along, there seems to be lots of different styles of videos in the way that the person was superimposed on the slides. In fact it was often impossible to read the text in the slide due to the size of the presenters head which obscured the text. Honestly this data science course is getting worse as the months progress, you really should think of updating the content of the course if you want to continue to charge money for it. 2 stars as I did actually learn something despite the quality of the material and its delivery.

by Brian S C

•Mar 01, 2016

Overall okay course but the lectures are too focused on theory with some applications to the real world. I think this course needs to be reconfigured and taught from an applied focus instead of 30% applied 70% theory.

Also the new format is horrible and TAs are nonexistent as are discussions in general on the forums now. The TAs were a critical learning component before especially considering that unlike on EdX where course staff actually participates in the forums, on Coursera I do not think I have ever observed course staff actively participating in the forums.

by Simon

•Sep 01, 2017

The concepts behind this course are really important. However, I feel that the material is not up to the needed level.

I am missing a good solid material that explains properly the theory behind these methods. I had to revert to other books (that could have well showed up as references in the course material) to get a proper understanding.

by 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!

by Daniel M G

•Jan 21, 2016

Un curso difícil de entender si no tienes la base matemática de regresión. Uno no sabe por dónde empezar, cualquiera de los cursos de esta serie (Statistical Inference, R programming...) pareciera que te saturan de información. Es bueno para curiosos con bases en R y que quieren saber más de Regresión

by Jing Z

•Feb 08, 2016

I just realized that you have to upgrade(pay $49) in order to submit the quiz and receive the feedback. That's depressing since my purpose is to watch the video and check out what I learned so far without getting any certificate. The policy here bring huge inconvenience for people like me.

by 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.

by 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?

by 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

by Jorge P

•Jun 07, 2016

Should cover a lot of dfificuties when the model assumptions are violated and should be for a longer time or having a second course about this theme.

by João R

•Aug 20, 2017

Needs more practical examples. Could be rerecorded. I love mathematical theory but past week 2 it is really too theoretical, in my opinion.

by Brian

•Feb 12, 2016

way to much emphasis on non-data science. This one course covers more information that the rest of the courses combined..

by Rich

•Mar 03, 2016

Very difficult. Needs homework problems guided by videos like Statistical Inference coarse to make easier.

by Albert B

•Jan 09, 2017

To fast pace and missing lot of content to make this lesson enjoyable!!!

by Rezoanoor/CS/Rezoanoor R

•Apr 20, 2020

The course was nowhere near of interesting. It was arduous and boring.

by Izabela E

•Aug 12, 2016

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

by Sepehr S

•Mar 11, 2016

The instructor is not good and doesn't explain things clearly.

by Daniel R

•May 14, 2016

Some topics that are important, are obviated

by Joseph D

•Apr 29, 2016

Coursera keeps changing my rating. Not cool.

by Ankit S

•Oct 24, 2018

not effective for new learnners

by 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.

by 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.

by Olivia U

•Jun 10, 2020

This is, by far, the worse course of the whole specialization. The instructor has a talent to make this whole topic way more complicated than it is. I ended up auditing the Duke University course on the same subject to understand the concepts, as well as watching many youtube videos, which allowed me to properly do the course project (which is the only good thing about this course: applying what you've learned). I cannot recommend this course to anyone if it's not as part of the specialization.

by Lawrence G

•Jun 06, 2020

The most worthless waste of my time this year. I learned more in an hour of browsing external sources than I did from the entirety of the course material, which was poorly structured and extremely dull. Were I not so heavily invested in this specialisation already, I would have cancelled my subscription over it.