Regression Models に戻る

4.4

2,790件の評価

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470件のレビュー

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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by Charbel L

•Aug 20, 2019

Very comprehensive introduction to regression models. Well done!

by Muhammad Z H

•Sep 15, 2019

learning alot

by BOUZENNOUNE Z E

•Sep 22, 2019

This was great. However, to follow it more precisely, you need the following: Read the book of linear regression from the same teacher. Usually a useful strategy would be to read each chapter first from the book, then watch the video associated to it, and finally do the swirl exercice.

You may need to follow the course notes of this class, they are published in github, and they can help a lot, especially for the quizzes.

by Naveen S

•Sep 06, 2019

really it is very good

by Rizwan M

•Sep 10, 2019

excellent courseware with assignments

by Сетдеков К Р

•Sep 30, 2019

It was rather hard and time consuming, but I learned a lot about poisson and binomial regressions.

by Connor B

•Sep 12, 2019

Learned a lot and enjoyed the course project. Would like to have two course projects because I gain the most out of them.

by Ashwin V

•Oct 11, 2019

great course

by Channaveer P

•Oct 12, 2019

Amazing course... good learning experience. Very useful for my role in my Organization.

by Dr. T A

•Oct 12, 2019

A good review of regression that allows the student to apply practical implementations in R Studio

by Giovanni G

•Oct 18, 2019

Very interesting

by gerson d o

•Nov 24, 2019

Wonderful!!!!

by Charles W

•Nov 27, 2019

If this was an on-campus course, I would have been a little worried about the quiz grades on the 1st try. However, with the ability to re-take this quizzes, I think this was an Excellent and well thought-out course.

by Boris K

•Oct 30, 2019

Along with the Statistical Inference Class and Building Predictive Models Class this is one of the best in this Specialization. It is reasonably tough, well-taught, overall great.

by Purificación V

•Nov 13, 2019

Es un gran curso para aprender, junto con el resto de los cursos de la especialización.

by Alzum S M

•Jan 08, 2019

Very much thank you for teaching me such an awesome course

by Nathalie D

•Mar 11, 2019

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

by 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.

by 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.

by Daniel J R

•Dec 19, 2018

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

by Dora M

•Mar 30, 2019

Good class.

by 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.

by 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).

by Pulkit K

•Jun 09, 2018

It lacked practical application, not impressed.

by Freddie K

•Jul 09, 2017

Really good! All the pieces from the previous courses start to come together into a whole.