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Voltar para Modelos Regressivos

Comentários e feedback de alunos de Modelos Regressivos da instituição Universidade Johns Hopkins

2,796 classificações
470 avaliações

Sobre o curso

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....

Melhores avaliações


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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276 — 300 de {totalReviews} Avaliações para o Modelos Regressivos

por Nevon L D

Sep 27, 2018

Builds Heavil

por Jamison R C

Aug 28, 2018

Excellent course, though I recommend you supplement applied practice by using the principal instructor, Dr. Brian Caffo's book, to answer practice questions if you want to retain these content-packed lessons. Better yet, begin each week by looking at the quiz and printing it out. As you view the relevant content, answer the related questions (which are generally presented in order of delivery).

por Yusuf E

Aug 15, 2018

I am almost certain that regression models have more relavance in an academic setting than industry. But this doesn't affect really how I graded this course. I wish Brian skipped over the first week which entirely deals with regression to the mean. Weeks 2 and 3 were very good and detailed.

I am not sure if logistic classifier is mentioned in the next course but it would probably be best if this part would be included in the ML course. Other than that great course and very challenging quizzes.

por Chonlatit P

Aug 19, 2018

Love this course. teach me to understand Linear Regression more, especially swirl class is great.

por ravi v

Oct 12, 2018

Overall a good course. But I was expecting more in depth covering of the topics.

por Kim K

Aug 08, 2018

You will need to know the subject before taking this class in order to understand or be able to put in a large amount of time to learn. The book "Introduction to Statistical Learning" is an excellent supplement to the course. Rigorous and rewarding when you put the work in.

por Martina H

Aug 19, 2016

Good course. My only negative remark is that I really missed the swirl exercises that were available for the other courses of this specialization.

por Camilo Y

Mar 14, 2017

Great introduction to regression models. Pretty clear

por Mariano F

Jun 12, 2016

Great course.

por Hang Y

Feb 08, 2017

Content regarding variable selection is kind of rough.

por Piotr K

Oct 23, 2016

Sometimes videos were hard to understand, especially in week 3.

por Mitraputra G

Jan 14, 2017

A little monotonous sometimes. Otherwise good.

por Jeremy J

Nov 12, 2016

Like the way the Prof uses media. This is a very light touch on a very deep subject so it has to balance analytical work with the light "trust me and just do it" approach. The balance was mostly there although on a couple items I don't know that I had a good enough grip to know what I don't know.

por Timothy V B

May 19, 2017

good intro

por Andrew W

Feb 20, 2018

Great subject, was a bit frustrated with some of the material (seemed rushed and not well prepared). Great assignment, but too restrictive on the max number of pages allowed. Wasted a lot of time.

por Mehul P

Oct 03, 2017

Easy way to understand Regression.

por Ada

Nov 14, 2016

Regression models was almost just as difficult as statistical inference. Again, the swirls and exercises were of great help. The pace, as always, was quite fast, but in the end all the pieces fitted together. Congratulations on a job well done!

por Karthik R

Aug 07, 2017

Knowledge on Statistics will help in better understanding.

por Nigel M

Sep 18, 2017

Good introduction to regressions and the process of applying regression analysis to data.

por Christopher B

Mar 01, 2017

This course was an improvement in teaching modality from the statistical inference course, with more polished content, but the link between the lectures and the actual exercises was still a bit strained. Overall, it felt like there was a bit of a disconnect between the swirl exercises and the lectures, and this led to a lot of self-teaching.

por Samirou T

May 26, 2018

I appreciate coefficients interpretation and variance influence to choose among models.

Running code takes a few seconds, understanding the model's outputs is a much hard

por Pulkit K

Jun 09, 2018

It lacked practical application, not impressed.

por Mingda W

Jun 05, 2018

Great, but need more examples and projects to practice the skills.

por Andrew W

Apr 05, 2018

Very good at presenting basic concepts. I highly reccomend saving the quiz questions as a good guide as to what you should know. I wish there were more material on generalized linear models.

por Sandro G

Jun 24, 2017

This is the first time that I take a course about regression models. I I found it very useful and enteresting, may be for someone who already know this argument it could be less useful, because in some part it is lacking. I mean above all about some example that could be a little bit more complex than those presented in the videos and that more probably it could be more similar to real cases. In anycase, I would like to thank a lot the teachers and courser for this occasion to learn given to me and others !