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Отзывы учащихся о курсе Регрессионные модели от партнера Университет Джонса Хопкинса

4.4
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Оценки: 2,980
Рецензии: 502

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

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.

Фильтр по:

351–375 из 482 отзывов о курсе Регрессионные модели

автор: César A C

Feb 03, 2018

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

автор: Marijus B

Apr 28, 2020

swirl exercises needs to be fixed, could not complete it because of the bug

автор: BIBHUTI B P

Jul 24, 2017

Wonderful experience of assimilating the techniques and tricks in this mod

автор: Sudheer P

Dec 28, 2016

This is a great course. The content clearly explains the regression model.

автор: Koen V

Sep 23, 2019

The explanation of the right answers from the quiz were quite handy!

автор: Humberto R

Feb 13, 2018

Great course. My prefered so far in the data science specialization

автор: Mingda W

Jun 05, 2018

Great, but need more examples and projects to practice the skills.

автор: antonio q

Mar 21, 2018

to me the more challenging course, well done though, thanks a lot

автор: Hariharan D

Sep 11, 2017

Intuitive course, liked it. Technical equations are challenging.

автор: 桂鹏

Jun 15, 2017

sufficient depth but explnation is not sufficient in many places

автор: Piotr K

Oct 23, 2016

Sometimes videos were hard to understand, especially in week 3.

автор: Alexandros A

Feb 08, 2016

I expected more in Binomial Regression and Poisson regression

автор: Yiyang Z

Aug 25, 2019

Very informative, but could be more interesting and concise.

автор: Manuel E

Jul 03, 2019

Hard class, documentation could be better, but good content.

автор: Alzum S M

Jan 08, 2019

Very much thank you for teaching me such an awesome course

автор: Pooia L

Sep 13, 2018

This is a very nice course provided you study a lot for it

автор: Karthik R

Aug 07, 2017

Knowledge on Statistics will help in better understanding.

автор: Luong M Q

Oct 17, 2017

some complicated contents that are hard to fully grasp.

автор: Hang Y

Feb 08, 2017

Content regarding variable selection is kind of rough.

автор: Camilo Y

Mar 14, 2017

Great introduction to regression models. Pretty clear

автор: Madhuri

Oct 26, 2016

prerequisites are very mandatory to do this course

автор: Pulkit K

Jun 09, 2018

It lacked practical application, not impressed.

автор: Mitraputra G

Jan 14, 2017

A little monotonous sometimes. Otherwise good.

автор: Mehrshad E

Dec 18, 2017

I found SWIRL more helpful than the lectures.

автор: Sameen S

Oct 02, 2018

The lectures were a bit complex and lengthy.