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Вернуться к Регрессионные модели

Отзывы учащихся о курсе Регрессионные модели от партнера Университет Джонса Хопкинса

Оценки: 3,306

О курсе

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....

Лучшие рецензии


16 дек. 2017 г.

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.


10 мар. 2019 г.

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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376–400 из 548 отзывов о курсе Регрессионные модели

автор: Nora M

1 дек. 2017 г.

Good course for basic regression. Would have enjoyed more time spent on properly interpreting results and how they are relevant to answering business questions.

автор: Roopak M

10 сент. 2018 г.

Nice course that helps make your foundations in regression modelling strong. The complexity of the course project can be increased to a more difficult level.

автор: Polina

29 июня 2018 г.

This course is a practical introduction to the regression models. Materials and organization are great, however slides and presentations require some work.

автор: Martina H

19 авг. 2016 г.

Good course. My only negative remark is that I really missed the swirl exercises that were available for the other courses of this specialization.

автор: Talant R

24 окт. 2016 г.

Great course to learn various regression models and "R" tools to implement them efficiently, but

was little hard to keep with the deadline.

автор: Jim B

27 апр. 2017 г.

Some lab work (swirl()) did not match the material presentation order. Essential coursework delivered at a blistering pace. Good Stuff.

автор: Mohamed T

19 мар. 2018 г.

Great course, learned a lot. The only point is that I was hoping to learn more about general linear models and its applications.

автор: Andrew

15 мая 2019 г.

Great introduction to regression models. A ton packed into the class. Be ready to be challenged, but you'll learn a lot.

автор: Pieter v d V

12 июня 2018 г.

Useful information about regression models, but to really understand the math you have to do a lot of googling yourself.

автор: Federico A V R

13 сент. 2017 г.

Would love to see more hands on practical explanations rather tan mostly slides.

Content is great though!

автор: Brian F

15 авг. 2017 г.

This a challenging course, overall I think it was good, but the material could be a bit better presented.

автор: Chonlatit P

18 авг. 2018 г.

Love this course. teach me to understand Linear Regression more, especially swirl class is great.

автор: Shakti P S

29 февр. 2016 г.

Good course. Prof. Caffo is a great teacher! Hope to see an advanced version of RegMods soon!

автор: Freddie K

9 июля 2017 г.

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

автор: Billy J

7 апр. 2016 г.

Videos were very difficult to follow along with. Overall, I learned a good amount though.

автор: Andrea G

10 янв. 2021 г.

A very good and comprehensive introduction to Regression Models with practical exercises.

автор: B S

2 июля 2018 г.

Nice course. It would however be better to include a summary how to approach an analysis.

автор: Nigel M

18 сент. 2017 г.

Good introduction to regressions and the process of applying regression analysis to data.

автор: Luiz E B J

26 нояб. 2019 г.

The content is to long, maybe would be interesting split the content in other modules.

автор: Deleted A

11 мар. 2019 г.

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

автор: Andrea S

25 февр. 2017 г.

Very good material but often too fragmentend/messy. The notes would need re-writing.

автор: Abrahan G U Ñ

10 февр. 2016 г.

It is a great introductory course into Regression analysis. I highly recommend it!

автор: Daniel J R

19 дек. 2018 г.

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

автор: Ravi V

12 окт. 2018 г.

Overall a good course. But I was expecting more in depth covering of the topics.

автор: César A C

3 февр. 2018 г.

Un curso bastante completo, aunque un pondría más ejemplos en la sección de GLM.