Chevron Left
Voltar para Modelos Regressivos

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

4.4
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

KA

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.

BA

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.

Filtrar por:

351 — 375 de {totalReviews} Avaliações para o Modelos Regressivos

por Yiyang Z

Aug 25, 2019

Very informative, but could be more interesting and concise.

por Wei W

Oct 23, 2017

Brian did better job in this course to elaborate and demonstrate with examples. No doubt Brian is extremely knowledge about this subject. Once again, this and Statistical Inference courses are very challenging to truly completed with insightful understanding. That's why I take one star away.

por Manpreet S

Oct 23, 2019

Good Course for beggining

por Prabesh S

May 06, 2016

Very intuitive course

por Sameen S

Oct 02, 2018

The lectures were a bit complex and lengthy.

por Koen V

Sep 23, 2019

The explanation of the right answers from the quiz were quite handy!

por Manojkumar P

Nov 08, 2016

Nice Course

por Linda W

Jun 04, 2016

This course will give you a good basic foundation in regression models. However, do be prepared to do a good amount of work besides just viewing the videos. I would recommend at the very least to go through the exercises in the 'recommended textbook' to gain a better understanding.

por Cesar L

Nov 01, 2016

Great course. The content might be improved to be more clear. I feel that sometimes the instructor assumes we are familiar with some concepts we have not seen in previous courses. Also, some times he does a very good job explaining the WHY before the HOW, and some other times he does not. Very knowledgeable instructor.

por Fernando L B d M

Sep 29, 2017

This time the professor Brian Caffo was more helpfull, explained better the concepts, and sometimes repeated some of the most important information... Good course!

por John D M

Apr 10, 2019

Overall an excellent course, but there were some issues with the wrong function being specified in one quiz (Q3q6) and the wrong answer in another. Apparently it has been that way for years, according to the forum. The quality of the lectures was very high and the information interesting, so compliments to Dr. Brian Caffo on that. However, the estimated time for completion of each week is ridiculously short compared to reality. Five hours? For me it was more like 20 hours, and more if I did all the Swirl exercises. Such low-balling on the time estimates is typical of the Data Science stream. The final project is given as 2 hours but it was closer to 15 for me. i wish Coursera would go back to the stream model where you could bump yourself to the next intake. That is much less stressful for busy working people like me.

por Anup K M

Oct 22, 2018

good content

por Talant R

Oct 25, 2016

Great course to learn various regression models and "R" tools to implement them efficiently, but

was little hard to keep with the deadline.

por BIBHUTI B P

Jul 24, 2017

Wonderful experience of assimilating the techniques and tricks in this mod

por Gianluca M

Oct 20, 2016

To me, this is by far the best course in the series. It deals with the scientific foundation of how to do data science: regression models, residuals, measures of the quality of the prediction, etc. The teacher is clearly a mathematician and has an academic style of presenting. He is very clear and chooses the subject in a clever way. One always understands what he or she is doing.

Highly recommended. It doesn't get five stars only because it covers only the basics; I would have really liked it to last twice as much!

por antonio q

Mar 21, 2018

to me the more challenging course, well done though, thanks a lot

por Luiz E B J

Nov 26, 2019

The content is to long, maybe would be interesting split the content in other modules.

por 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.

por Satish V

Apr 08, 2019

The instructor's delivery and content, although very professorial was very dry. For students who don't have that much of a background in regression and statistical inference, I think it would be good to get to the gist/summary - i.e the what (what kind of problem we are trying to solve) and the how (how to do it in R and more importantly how to interpret the results).

por Mertz

Mar 20, 2018

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

por Angela W

Nov 27, 2017

I learned a lot, but it was so much content for 4 weeks!

por 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 :-(

por Raphael R

Oct 31, 2016

I am no used to this educational system so I find difficult to follow without any proof or demonstration of the mathematical tools. I find proofs necessary for a good understanding of concepts. Another benefit of proof will be to have a more rigorous framework for variable names in the explanations. Even though this is more a practical course, it will benefit from being a bit more rigorous ; so at least people can make proofs on they own.

Other than that, it is a great course. Very practical and to the point.

por Gareth S

Jul 16, 2017

Expects a level of statistical knowledge already.

por Asif M A

Oct 23, 2016

I enjoyed the earlier courses more. I did not like the way the materials were provided. There were a lot of very complex ideas were presented, in a very concise and brief manner. Also, there should be more exercises to practice. May be its me, but, I guess, I might need more time to fully comprehend the materials.