Chevron Left
Regression Models に戻る

ジョンズ・ホプキンズ大学(Johns Hopkins University) による Regression Models の受講者のレビューおよびフィードバック

4.4
2,796件の評価
470件のレビュー

コースについて

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....

人気のレビュー

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.

フィルター:

Regression Models: 101 - 125 / 450 レビュー

by Gregorio A A P

Aug 26, 2017

Excellent, but I would be grateful if you could translate all your courses of absolute quality into Spanish.

by Jay S

Jul 29, 2016

Very informative and detailed explanation of how regression model works!

by Magnus G A

Feb 14, 2017

Great Course

by 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.

by 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.

by Bhopal

Jan 16, 2017

Very good course.

by Edmund J L O

May 12, 2016

I like this course a lot because it solidified my understanding of regression. I have often read about regression when reading scientific articles however, i never took the time to really investigate the mechanics on how it is done. Thanks to this course i can now appreciate better the journals that i read. Furthermore, the course project for this course was quite interesting, not too hard, and was bit challenging. There was plenty of time to finish the project and some extra time to make it even better than a simple submission that meets the basic requirements of the course. Thanks to the my classmates and the nice people in Coursera and R, i had a great time learning during this course.

by Harris P

Dec 19, 2016

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

by Chris W

Nov 27, 2016

Great course.

by Andrew K

Mar 13, 2017

Good foundation in the Data Science Certification for Practical Machine Learning. There are 3 areas that I would like to dig deeper so far: Statistical Inference, Regression Models and Practical Machine Learning (perhaps + Deep Learning).

by Albert C G

Sep 02, 2016

Great - learned a bunch

by Farhan M

Feb 26, 2017

Amazing course, I learnt a lot.

by Sai S S

Jul 09, 2017

Thanks much. Good course. Would have loved a tougher final project (eg. using logistic regression). How about adding two variants for all final projects - 1. lots of things to do vs. 2. more technically complex ?

by Berthold J

Jun 24, 2017

Very good lecture and also decent level of difficulties that requires to think/read additional stuff.

by Pragya k

May 22, 2017

Exceptional Learning!

by Andrew V

May 15, 2017

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

by Fernando M

Sep 04, 2017

Love it

by Lawar S V

Apr 19, 2017

Very Good Course !

by Muzaffar H

Oct 14, 2017

A very good data analysis course, highly useful for quantitative method and empirical findings.

by Joonas S

May 29, 2017

Really good introduction to regression models.

by Artem V

May 16, 2017

Complicated but good information!

by 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.

by Handong D B

Aug 15, 2016

very concise and well taught

by Amelia L

Nov 29, 2016

Learned a lot

by Yubo Y

Apr 03, 2016

concise, practical and straight forward