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Отзывы учащихся о курсе Регрессионные модели от партнера Университет Джонса Хопкинса

4.4
звезд
Оценки: 3,275
Рецензии: 564

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

KA
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.

DA
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!

Фильтр по:

151–175 из 545 отзывов о курсе Регрессионные модели

автор: Sandhya A

2 июня 2018 г.

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

автор: Christian H

22 авг. 2017 г.

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

автор: Roberto D

21 июня 2017 г.

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

автор: Harris P

19 дек. 2016 г.

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

автор: Erich F G

20 мар. 2018 г.

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

автор: Carlos A C Z

15 янв. 2018 г.

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

автор: Raunak S

10 нояб. 2018 г.

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

автор: Zhiming

26 сент. 2017 г.

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

автор: SATHYANARAYANAN S

10 сент. 2017 г.

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

автор: Vitalii S

20 июля 2017 г.

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

автор: Joe B

30 янв. 2016 г.

Great course with a thorough introduction to regression and linear model.

автор: Jay S

29 июля 2016 г.

Very informative and detailed explanation of how regression model works!

автор: Mayank C

25 февр. 2016 г.

Very comprehensive course for developing the basics of regression models

автор: Mateo C T

11 февр. 2021 г.

Excellent course, gives the necessary inputs to start in this matter.

автор: Shubham S Y

26 июня 2017 г.

Good for clearing out your basic Regression doubts and that too in R!

автор: Kyle H

2 апр. 2018 г.

A great, quick treatment of the major touch points of linear models.

автор: N S N

2 янв. 2018 г.

Very Exciting Journey of learning and thoroughly enjoyed the course.

автор: Sabawoon S

12 сент. 2017 г.

Excellent course, it could be improved with more practical examples.

автор: Rodrigo P

3 авг. 2017 г.

Very interesting topics and discussions, but not easy to understand.

автор: Bojan B

14 окт. 2018 г.

Great course with great materials. Easy to understand and to learn.

автор: 陈颐欢

29 июня 2018 г.

Basic idea about regression , it's very useful for beginner like me

автор: Wesley E

15 февр. 2016 г.

Great introduction and plenty of resources for more in depth study.

автор: Ayushmaan D V

4 авг. 2020 г.

This course serves as a great introduction to regression modelling

автор: Amanyiraho R

13 янв. 2020 г.

Gives you the best understanding of the roots of regression models

автор: Illich M

15 июня 2017 г.

Tough course! I had to take it a couple of times to understand it.