Voltar para Modelos Regressivos

4.4

2,704 classificações

•

456 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 桂鹏

•Jun 15, 2017

sufficient depth but explnation is not sufficient in many places

por Benjamin G J

•Jan 05, 2016

This is the best course of the bunch so far. These courses are really promising -- I've learned a lot from them and they probably have everything they could have at the price - but I'm leaving just one star off because I feel very strongly that some effort could really go a long way to making a better language map of these courses. A person leaves this course, and even more so the inference course, not being very clear one where their new capabilities lie in the spectrum, and without the strongest sense of how to experiment with linear models.

One case in point of the the huge strengths and a slight weakness of this course -- Professor Caffo mentions the wonderfully tantalizing fact that the application of linear models can get you most of the way to the top of a Kaggle competition. That feels true, I trust him, and it's really cool. But it would be SO. MUCH. COOLER. with an article showing a linear model attacking that kind of problem.

por Abrahan G U Ñ

•Feb 11, 2016

It is a great introductory course into Regression analysis. I highly recommend it!

por Romain F

•Apr 01, 2017

Great course, although feeling as always a bit rushed on the last lectures. At least it makes you want to investigate more about the subject.

I find frustrating however not to have a proper instructor example of the final assignment, it is hard to review other participants work and realize what they / you have done wrong without actually knowing how best the assignment should have been fulfilled.

And as all courses in this specialization, there is not much interaction between participants, and not much effort by mentors to animate it

por Arturo M K

•Dec 10, 2016

I was hoping to learn about PROBIT models. I know they are very similar to LOGIT ones, but still... the pace is a little bit too fast and I think it requires more time than what it says.

por Vidya M S

•Mar 14, 2017

The concepts are well explained and precise. I think it depends on the individual to dive deeper into the topic by independent learning. Good data examples. Also following the suggested book of the author helps with some extra excercises. However , I feel extra practice questions would help .

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 Utkarsh Y

•Sep 28, 2016

It is a good course for learning regression model implementation in R. You may need to have a basic understanding of popular regression models like linear & logistic as the course doesn't cover mathematical aspects in detail

por Shakti P S

•Feb 29, 2016

Good course. Prof. Caffo is a great teacher! Hope to see an advanced version of RegMods soon!

por Polina

•Jun 29, 2018

This course is a practical introduction to the regression models. Materials and organization are great, however slides and presentations require some work.

por Norman B

•Feb 08, 2016

A decent overview of regression

por Alexandros A

•Feb 08, 2016

I expected more in Binomial Regression and Poisson regression

por Kevin H

•Nov 09, 2016

Something was missing from this course. I cam away with an increased understanding of regression but I still feel like I struggle with many concepts and had to put in much more time than the recommended.

Still when I found the answer it was all still contained and maybe the material itself is just advanced.

my 2c

por David E L B

•May 18, 2017

Really helpful and well presented.

por Yuekai L

•Mar 07, 2016

Nice.

por Pawel D

•Dec 18, 2016

This course is much improved, when compared with Statistical Inference. The instructor have put much effort in making the lectures interesting and casual, at the same time not loosing the value of contents. I especially liked some subtle jokes - just a finishing human touch.

Some lectures from 4th week were not very well rehearser and shot hastily. Some quiz question were disproportionately difficult, but most of material is covered in course or course materials. Otherwise the course is very educational.

por Luong M Q

•Oct 17, 2017

some complicated contents that are hard to fully grasp.

por B S

•Jul 02, 2018

Nice course. It would however be better to include a summary how to approach an analysis.

por Federico A V R

•Sep 14, 2017

Would love to see more hands on practical explanations rather tan mostly slides.

Content is great though!

por Teppakorn

•Jun 22, 2016

Advance topic in regression model.

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 Ankush K

•Jan 16, 2018

really informative with helpful examples.

por Richard M A

•Dec 23, 2016

This was better than the statistical inference course, but Brian still puts too much emphasis on the precision of his language (as if he's teaching to other mathematicians) which makes it difficult to understand. I would like to see a bit more dumbed down explanation of the mathematics in the examples (similar to Sal at Khan Academy). If that happened, this would definitely be a 5 star course.

por Manojkumar P

•Nov 08, 2016

Nice Course

por Billy J

•Apr 07, 2016

Videos were very difficult to follow along with. Overall, I learned a good amount though.