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Avis et commentaires pour d'étudiants pour Modèles de régression par Université Johns-Hopkins

4.4
étoiles
3,073 évaluations
511 avis

À propos du cours

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....

Meilleurs avis

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.

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76 - 100 sur 496 Avis pour Modèles de régression

par Pedro C D

Nov 15, 2018

Impressive! Very detailed in statistics and Mathematics, I would like an extensive course in logistic regression, it was short compared with lm course.

par Maxim M

Dec 10, 2017

A very good course, goes deeply into the material. The pace of the professor is ok. It's nice that he uses some practical cases to explain the theory.

par Jorge B S

Jun 20, 2019

I have loved this introductory course about Regression. The swirl exercises are especially useful to revise the course content and apply the theory.

par 20e

Aug 06, 2018

Helpful!

If there is more introduction about the common problems people may encounter during working in the real world, the course will be better!

par Paul F G

Jun 13, 2018

Excellent, highly focused course with current R libraries for learning various regression methods and methodology. I highly recommend this course.

par 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.

par Hernan D S P

May 19, 2018

This course is perfect to get started with Regression Models in R! I think you would need some familiarity with the statistical concept though.

par Reza M

Jun 21, 2020

Excellent course on regression modelling it showcases the power of R. quite a heavy module though for people with none statistical background

par Kumar G G

May 01, 2017

I think this is the best course I have ever came across in the coursera. Everything is discussed in the most simple manner with great depth.

par Shivendra S

Mar 04, 2017

In-depth and detailed, this one month course will provide aspirants with the knowledge and skills required to conduct efficient regressions.

par Lopamudra S

Nov 30, 2017

The Regression Models is an excellent course for a beginner.I would recommend the enthusiastic students for a great start in Data science.

par Emanuele M

Aug 11, 2016

It's a great course and tought very well. It required effort, you apply many of previously teach concept and requires a lot of excercise

par Abhinav G

Jun 28, 2017

Very Helpful course. I am from a non -stats background and this has helped me a lot in understanding such deep concepts of Statistics.

par MEKIE Y R K

May 02, 2019

Really interesting and full of advices.

But would like to dig more into the Logistic and poisson regression residuals explanations :)

par Matthew C

Nov 21, 2017

Week 4 was a lot harder than the other weeks (specifically the quiz). Overall, a lot of great information packed into this month.

par Sandra Y M B

Oct 09, 2016

Everything you need to know to have a clear understanding of regression models and learn how to use their basic functions in R.

par Damien C

Dec 06, 2016

Great ressources. Usefull presentations, maybe too rich for a newbie.

It was too fast for me. Could be done in 2x more time :/

par Richard F

Jun 18, 2017

This is the most challenging course so far - new concepts, new approaches and application to a wide variety of situations.

par 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.

par Carlos M B B

Jun 20, 2017

Thank you for the chance to review all the fundamental and applied mathematical and statistical aspects of data analysis.

par Stefan S

Mar 04, 2016

Not the easiest course, but very rewarding if you hang in there. The material is very well explained with ample examples.

par Nino P

May 24, 2019

Similarly to statistical inference, this is a bit harder course in the specialization. Still passable and recommendable.

par German R M S

Jun 07, 2018

Excelente curso, requiere de esfuerzo y dedicación, ademas de una solida base estadística. Práctico y de mucha utilidad.

par Daniel A S

Jun 10, 2020

Very good and complete, the professor is very clear in his explanations and very helpful for data science applications.

par Ekaterina S

May 12, 2019

It was a very usefull course. It is a very good approach to the theme - the main essence without much math difficulty.