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 Charbel L

•Aug 20, 2019

Very comprehensive introduction to regression models. Well done!

por Daniel J R

•Dec 19, 2018

Quite practical. It does encourage one to follow-up with a more advanced course.

por David J B

•Feb 19, 2019

Probably the most conceptually challenging and practically useful course in the JH data science certification series (so far... I have a few more courses to complete).

por Manny R

•Mar 22, 2019

Really Fun Course. There is a lot to learn in this topic and this could be studied for a lifetime. I feel like I could apply this to discover solutions for issues at work.

por Dora M

•Mar 30, 2019

Good class.

por Don 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 Paul R

•Mar 13, 2019

Relatively, this is one of the best courses and lecturers of the specialization, Brian delivers clear, thorough and well-paced lectures. These lectures on statistics, regression and machine learning are where the rubber hits the road after a lot of prep work to learn R and principles/tools of data science taught in earlier classes.

por Alzum S M

•Jan 08, 2019

Very much thank you for teaching me such an awesome course

por Nathalie D

•Mar 11, 2019

Great course, but please check those subtitles that are occasionally completely off!

por Roopak M

•Sep 10, 2018

Nice course that helps make your foundations in regression modelling strong. The complexity of the course project can be increased to a more difficult level.

por Pooia L

•Sep 13, 2018

This is a very nice course provided you study a lot for it

por Daniiar B

•Sep 27, 2018

Very hard to understand

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 Anup K M

•Oct 22, 2018

good content

por ravi v

•Oct 12, 2018

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

por Sameen S

•Oct 02, 2018

The lectures were a bit complex and lengthy.

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 Prabesh S

•May 06, 2016

Very intuitive course

por Mariano F

•Jun 12, 2016

Great course.

por Hang Y

•Feb 08, 2017

Content regarding variable selection is kind of rough.

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