Voltar para Modelos Regressivos

4.4

2,671 classificações

•

450 avaliações

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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por 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.

por 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

por 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.

por 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?

por 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.

por Sepehr S

•Mar 11, 2016

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

por 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.

por 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.

por 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

por Albert B

•Jan 09, 2017

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

por Rich

•Mar 03, 2016

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

por 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.

por 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.

por Barry S

•Mar 15, 2016

This course is the first one in the Data Science series to lapse in terms of the clarity of the lectures, and the sense of cohesiveness of the material. Brian Caffo's lectures in Statistical Inference were good; in this course they seem to veer left and right rather than get straight to the essence of whatever subject he is lecturing about.

A more structured final project would have been helpful. The instructions on this project weren't quite so blunt as to say "Take this data set, do some regression-y stuff and come back with something about these two variables," but that's basically as far as our instructions went. It could have been a great learning experience to have a more detailed guide through the construction of a regression analysis, but instead an assignment which was 40% of our grade was put together as an afterthought. It was the assignment equivalent of stopping in the 7-11 a block away from a birthday party to buy a card.

Also, in terms of delivering the content: Mr. Caffo needs to structure his slide/video arrangements so that he is not standing in front of the text. Think of it from the point of view of somebody wanting to listen and read at the same time.

por 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.

por 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..

por 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.

por 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!

por Shahryar N

•Nov 29, 2018

The course is awfully simplified.

por 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.

por 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.

por Eric T

•Feb 21, 2017

Important material, poorly taught.

por 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.

por 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.

por 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.

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