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Volver a modelos de regresión

Opiniones y comentarios de aprendices correspondientes a modelos de regresión por parte de Universidad Johns Hopkins

3,307 calificaciones

Acerca del Curso

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....

Principales reseñas


16 de dic. de 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.


10 de mar. de 2019

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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401 - 425 de 549 revisiones para modelos de regresión

por Scipione S

14 de jul. de 2020

I suggest to revie some videos. There is some repetition, especially in week 3.

por Marijus B

28 de abr. de 2020

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


24 de jul. de 2017

Wonderful experience of assimilating the techniques and tricks in this mod

por Sudheer P

28 de dic. de 2016

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

por Koen V

23 de sep. de 2019

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

por Humberto R

13 de feb. de 2018

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

por Mingda W

5 de jun. de 2018

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

por antonio q

21 de mar. de 2018

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

por Hariharan D

11 de sep. de 2017

Intuitive course, liked it. Technical equations are challenging.

por 桂鹏

15 de jun. de 2017

sufficient depth but explnation is not sufficient in many places

por Piotr K

23 de oct. de 2016

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

por Frank O

12 de jul. de 2021

Mathematically difficult topic for me, but very well conveyed

por Alexandros A

8 de feb. de 2016

I expected more in Binomial Regression and Poisson regression

por Yiyang Z

24 de ago. de 2019

Very informative, but could be more interesting and concise.

por Manuel E

3 de jul. de 2019

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

por Alzum S M

8 de ene. de 2019

Very much thank you for teaching me such an awesome course

por Pooia L

13 de sep. de 2018

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

por Karthik R

7 de ago. de 2017

Knowledge on Statistics will help in better understanding.

por Luong M Q

16 de oct. de 2017

some complicated contents that are hard to fully grasp.

por H Y

8 de feb. de 2017

Content regarding variable selection is kind of rough.

por Camilo Y

14 de mar. de 2017

Great introduction to regression models. Pretty clear

por Madhuri

26 de oct. de 2016

prerequisites are very mandatory to do this course

por pulkit k

9 de jun. de 2018

It lacked practical application, not impressed.

por Mitraputra G

14 de ene. de 2017

A little monotonous sometimes. Otherwise good.

por Mehrshad E

18 de dic. de 2017

I found SWIRL more helpful than the lectures.