Chevron Left
Back to Regression Models

Learner Reviews & Feedback for Regression Models by Johns Hopkins University

4.4
stars
3,165 ratings
529 reviews

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

MM
Mar 12, 2018

Great course, very informative, with lots of valuable information and examples. Prof. Caffo and his team did a very good job in my opinion. I've found very useful the course material shared on github.

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.

Filter by:

126 - 150 of 510 Reviews for Regression Models

By Guilherme B F

Mar 22, 2018

Really good. Easy to follow and great even if you just need a refresher in regression models.

By Arcenis R

Jan 18, 2016

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

By ric j n

Aug 6, 2017

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

By Georgios P

Mar 7, 2019

Great course for beginners, but definitely not for people with no mathematical background!

By sneha

Jan 23, 2019

Amazing course ! finally I have learned how to implement regression in real world analysis

By Carlos A R C

Sep 23, 2020

Excellent course. Best of all the Data Science specialization. Good, very good professor.

By Bruno R S

Mar 4, 2019

A deep review on linear, logistic and regression models. The critical tool for modelling.

By Walter T

Dec 8, 2016

A well defined learning path to understand the fundation of machine learning techniques.

By Purificación V

Nov 13, 2019

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

By Channaveer P

Oct 12, 2019

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

By Juan P L R

Nov 26, 2020

Great introduction to regression models, and its application in R. Highly recommended.

By Andrew V

May 14, 2017

Nicely presented and understandable course with a challenging an interesting project.

By BAUYRJAN J

Jan 31, 2017

Excellent course, but you have to use other materials from different courses as well.

By Johan V M

Aug 9, 2020

Excellent course! I am totally looking forward to learn a lot more on this subject.

By Sergio A

Dec 31, 2017

We learn some basic econometrics in this class and how to do basic regression mdels

By Sandhya A

Jun 1, 2018

Learned a lot about various regression model, concept like fitting and overfitting

By Christian H

Aug 22, 2017

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

By Roberto D

Jun 21, 2017

Concepts explained and illustrated very well to understand how variables differ.

By Harris P

Dec 19, 2016

Was tough but thoroughly had fun completing it. Its a cleverly designed course.

By Erich F G

Mar 20, 2018

Challenging course. Brought back memories of graduate school in the early 90s

By Carlos A C Z

Jan 15, 2018

This was a good course. I learn a lot making the final Project of the course

By Raunak S

Nov 10, 2018

a very good course before digging deeper into Data Science advanced topics.

By Tai C M

Sep 26, 2017

This course is not as tough as the statistics class. Easier to understand.

By SATHYANARAYANAN S

Sep 10, 2017

Very good for anyone wanting to get into the field of Data Science using R

By Vitalii S

Jul 20, 2017

I liked this course, but I would like that last task be more complicated.