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.

필터링 기준:

교육 기관: Christian H

•Aug 23, 2017

Great course; practical introduction to regression models at the university level.

교육 기관: Juliusz G

•Nov 21, 2016

Very practical/hands-on intro to regression models. You will definitely be able to apply those methods after this course whenever you need them.

교육 기관: Arcenis R

•Jan 18, 2016

This course is packed with great lessons and Prof. Caffo puts it all together very cogently.

교육 기관: Manuel X D

•Feb 09, 2016

Data, our “raw” material, becomes plentiful. Let’s learn form it.

Thanks to constant progress in information technologies, this increasing production of data is an outstanding opportunity to improve our knowledge of subject matters we care about, e.g. environment, health, markets…

Properly analyzing these data in the scope of addressing specific questions is not trivial. But it can be learn. And if there were one place where one could acquire these skills and become anxious to grow in that field, this would be the Coursera Regression Models course. Data analysts, like any professionals, need her/his set of tools. Good tools make good patricians. The Coursera Data Science Specialization that includes this Regression Models class is where one can learn how to use the right tools and reduce them into practice. Passionate instructors who obviously take great care in communicating effectively the knowledge they master teach these courses admirably. Highly recommended course and specialization,

There are so many unanswered questions, so many new relationships to uncover. Learn how.

교육 기관: Marco B

•Dec 21, 2017

very useful! it provides both theoretical framework and practical skills!

it helped me improve my daily data analysis!

교육 기관: Nirav D

•Mar 05, 2016

I loved studying Regression Models taught by Prof. Brian Caffo. I think these are very important techniques that I will be able to use for my research and analysis.

I found the teaching to be very in depth in explaining various aspects of regression model development.

교육 기관: Joseph R

•Mar 03, 2016

A very well organized course with nice simple explanations and introductions into the world of regression models

교육 기관: Veronica F V M

•Nov 23, 2017

Muy bueno :)

교육 기관: weitinglin

•Oct 28, 2016

nice and practical class! I think if provide some recommend reading may create more deeper insight in regression

교육 기관: ric j n

•Aug 06, 2017

The course is comprehensive in its presentation. Ideas can be easily grasp and replicated.

교육 기관: Charles-Antoine d T

•Oct 29, 2017

amazing

교육 기관: Kristin A

•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.

교육 기관: Francisco J D d S F G

•Nov 03, 2016

Love the whole course approach on the importance of linear models and how one should interpret them to get a better grasp of the data one possesses - one should definitely take the statistical inference course before attempting this course beforehand.

교육 기관: Anang H M A

•Nov 21, 2017

Great course.

교육 기관: Chris

•Dec 22, 2017

good class.

교육 기관: Ivan Y

•Feb 14, 2018

I learned a lot through this course! It's not easy, and there's a lot of technical details that required me to watch the videos 2-3 times through to have a proper grasp, but super helpful stuff!

교육 기관: Wei L

•Oct 12, 2017

A lot of good info. Some of them is a little hard to me

교육 기관: Samiul A

•Jan 12, 2017

Excellent course.

교육 기관: Sai K G

•Feb 01, 2016

Course teaches basics of regression in R

교육 기관: Jose A R N

•Nov 06, 2016

My name is Jose Antonio from Brazil. I am looking for a new Data Scientist career (https://www.linkedin.com/in/joseantonio11)

I did this course to get new knowledge about Data Science and better understand the technology and your practical applications.

The course was excellent and the classes well taught by teachers.

Congratulations to Coursera team and Instructors

교육 기관: Chris

•Nov 02, 2016

great introduction to regression models

교육 기관: Larry G

•Feb 07, 2017

Nice

교육 기관: Jared P

•Apr 10, 2017

With the first few videos, I was concerned I would be re-living the nightmare that was the Statistical Inference course. (I gave a long review of that one. To summarize Statistical Inference: I hated it. But I learned things. Those things stuck. I used them in real life. That's good.)

But wow, after getting through this course, I loved it. Very practical and useful stuff. It had me thirsting for more information and I found myself reading unassigned material. I became particularly interested in Anova and continuing to read up on it even though I am done the course.

I would take this course again. I would recommend it to those wanting to learn more about data science. It's got some quirks and room for improvement, but overall it's a good course.

교육 기관: Paula L

•Dec 02, 2016

good review of the fundamentals

교육 기관: Kpakpo S M

•Jul 26, 2017

Perfect course toward the data science specialization. It gives good understanding and improve my knowledge of inference statistic. I have the opportunity to explore all the plotting concept and apply them in regression models arena.Good to take this course to step in the concept of machine learning.