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Learner Reviews & Feedback for Regression Models by Johns Hopkins University

4.4
stars
3,358 ratings

About the Course

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....

Top reviews

KA

Dec 16, 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.

DA

Mar 10, 2019

This module was the maximum. I learned how powerful the use of Regression Models techniques in Data Science analysis is. I thank Professor Brian Caffo for sharing his knowledge with us. Thank you!

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76 - 100 of 559 Reviews for Regression Models

By Connor G

Sep 18, 2017

Extremely valuable content to my pursuit of a career in data science. This, paired with the Machine Learning, are giving me great insights into predictive analytics.

By Ioannis B

Aug 1, 2017

Exceptional course for the subject of Regression. You can really understand the foundations and build on it with R. Congratulations to the instructors and the team.

By Elena C

Mar 3, 2017

A very intense course, where a lot of concepts are introduced. In order for all the new information to be metabolized, it took me much more than four weeks.

By 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.

By 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.

By 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.

By 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

By Kumar G G

May 1, 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.

By Shivendra S

Mar 4, 2017

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

By 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.

By James E

Aug 3, 2021

Thorough material with challenging quizzes means that you finish this course feeling like you genuinely have a good handle on the topic.

By MEKIE Y R K

May 2, 2019

Really interesting and full of advices.

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

By Matthew C

Nov 20, 2017

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

By Sandra M

Oct 9, 2016

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

By Aida B S H

Apr 21, 2021

Regression analysis has been a very insteresting course. I've learned a lot, and was happy to do my graphs and analysis in R!

By Damien C

Dec 6, 2016

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

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

By Richard F

Jun 17, 2017

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

By Carlos B

Jun 19, 2017

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

By Stefan S

Mar 4, 2016

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

By Nino P

May 24, 2019

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

By Rafael M

Jun 7, 2018

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

By Vitor P B

Oct 25, 2020

Very detailed and complete course with heavy theorical concepts which are all very useful for data science applications

By 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.

By Georgeanne P

May 31, 2021

This is a tough course. I needed to use materials outside of the course to get the full understanding. But is it good.

By 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.