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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:

76–100 из 545 отзывов о курсе Регрессионные модели

автор: Daniel C J

2 авг. 2017 г.

Great introductory course on Regression Models. Super practical and well explained. Definitely doing the exercises and final project is a must to get all the learnings!

автор: Sindre F

1 авг. 2016 г.

Interesting and important course!

I don't think this course is suitable for beginners. You need to know this stuff before you take the course. Works well as a refresher.

автор: Aisha H

2 февр. 2016 г.

Loved the course and the content. Only critique is that I would have liked to have a lecture about transformations, and interpretation of transformed data coefficients.

автор: Connor G

18 сент. 2017 г.

Extremely valuable content to my pursuit of a career in data science. This, paired with the Machine Learning, are giving me great insights into predictive analytics.

автор: Ioannis B

1 авг. 2017 г.

Exceptional course for the subject of Regression. You can really understand the foundations and build on it with R. Congratulations to the instructors and the team.

автор: Samy S

25 февр. 2016 г.

Good introduction to the usefulness and traps of linear models. By the way, having the teacher filmed for the lectures does provide a more engaging experience.

автор: Elena C

3 мар. 2017 г.

A very intense course, where a lot of concepts are introduced. In order for all the new information to be metabolized, it took me much more than four weeks.

автор: Pedro C D

15 нояб. 2018 г.

Impressive! Very detailed in statistics and Mathematics, I would like an extensive course in logistic regression, it was short compared with lm course.

автор: Maxim M

10 дек. 2017 г.

A very good course, goes deeply into the material. The pace of the professor is ok. It's nice that he uses some practical cases to explain the theory.

автор: Jorge B S

20 июня 2019 г.

I have loved this introductory course about Regression. The swirl exercises are especially useful to revise the course content and apply the theory.

автор: 20e

6 авг. 2018 г.

Helpful!

If there is more introduction about the common problems people may encounter during working in the real world, the course will be better!

автор: Paul F G

12 июня 2018 г.

Excellent, highly focused course with current R libraries for learning various regression methods and methodology. I highly recommend this course.

автор: Juliusz G

21 нояб. 2016 г.

Very practical/hands-on intro to regression models. You will definitely be able to apply those methods after this course whenever you need them.

автор: Hernan S

19 мая 2018 г.

This course is perfect to get started with Regression Models in R! I think you would need some familiarity with the statistical concept though.

автор: Reza M

21 июня 2020 г.

Excellent course on regression modelling it showcases the power of R. quite a heavy module though for people with none statistical background

автор: Kumar G G

1 мая 2017 г.

I think this is the best course I have ever came across in the coursera. Everything is discussed in the most simple manner with great depth.

автор: Shivendra S

4 мар. 2017 г.

In-depth and detailed, this one month course will provide aspirants with the knowledge and skills required to conduct efficient regressions.

автор: Lopamudra S

30 нояб. 2017 г.

The Regression Models is an excellent course for a beginner.I would recommend the enthusiastic students for a great start in Data science.

автор: James E

3 авг. 2021 г.

T​horough material with challenging quizzes means that you finish this course feeling like you genuinely have a good handle on the topic.

автор: Emanuele M

11 авг. 2016 г.

It's a great course and tought very well. It required effort, you apply many of previously teach concept and requires a lot of excercise

автор: Abhinav G

28 июня 2017 г.

Very Helpful course. I am from a non -stats background and this has helped me a lot in understanding such deep concepts of Statistics.

автор: MEKIE Y R K

2 мая 2019 г.

Really interesting and full of advices.

But would like to dig more into the Logistic and poisson regression residuals explanations :)

автор: Matthew C

20 нояб. 2017 г.

Week 4 was a lot harder than the other weeks (specifically the quiz). Overall, a lot of great information packed into this month.

автор: Sandra M

9 окт. 2016 г.

Everything you need to know to have a clear understanding of regression models and learn how to use their basic functions in R.

автор: Aida B S H

21 апр. 2021 г.

Regression analysis has been a very insteresting course. I've learned a lot, and was happy to do my graphs and analysis in R!