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ジョンズ・ホプキンズ大学(Johns Hopkins University) による Regression Models の受講者のレビューおよびフィードバック

4.4
2,796件の評価
470件のレビュー

コースについて

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....

人気のレビュー

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.

フィルター:

Regression Models: 276 - 300 / 450 レビュー

by Nevon L D

Sep 27, 2018

Builds Heavil

by Jamison R C

Aug 28, 2018

Excellent course, though I recommend you supplement applied practice by using the principal instructor, Dr. Brian Caffo's book, to answer practice questions if you want to retain these content-packed lessons. Better yet, begin each week by looking at the quiz and printing it out. As you view the relevant content, answer the related questions (which are generally presented in order of delivery).

by Yusuf E

Aug 15, 2018

I am almost certain that regression models have more relavance in an academic setting than industry. But this doesn't affect really how I graded this course. I wish Brian skipped over the first week which entirely deals with regression to the mean. Weeks 2 and 3 were very good and detailed.

I am not sure if logistic classifier is mentioned in the next course but it would probably be best if this part would be included in the ML course. Other than that great course and very challenging quizzes.

by Chonlatit P

Aug 19, 2018

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

by ravi v

Oct 12, 2018

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

by Kim K

Aug 08, 2018

You will need to know the subject before taking this class in order to understand or be able to put in a large amount of time to learn. The book "Introduction to Statistical Learning" is an excellent supplement to the course. Rigorous and rewarding when you put the work in.

by Martina H

Aug 19, 2016

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

by Camilo Y

Mar 14, 2017

Great introduction to regression models. Pretty clear

by Mariano F

Jun 12, 2016

Great course.

by Hang Y

Feb 08, 2017

Content regarding variable selection is kind of rough.

by Piotr K

Oct 23, 2016

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

by Mitraputra G

Jan 14, 2017

A little monotonous sometimes. Otherwise good.

by Jeremy J

Nov 12, 2016

Like the way the Prof uses media. This is a very light touch on a very deep subject so it has to balance analytical work with the light "trust me and just do it" approach. The balance was mostly there although on a couple items I don't know that I had a good enough grip to know what I don't know.

by Timothy V B

May 19, 2017

good intro

by Andrew W

Feb 20, 2018

Great subject, was a bit frustrated with some of the material (seemed rushed and not well prepared). Great assignment, but too restrictive on the max number of pages allowed. Wasted a lot of time.

by Mehul P

Oct 03, 2017

Easy way to understand Regression.

by Ada

Nov 14, 2016

Regression models was almost just as difficult as statistical inference. Again, the swirls and exercises were of great help. The pace, as always, was quite fast, but in the end all the pieces fitted together. Congratulations on a job well done!

by Karthik R

Aug 07, 2017

Knowledge on Statistics will help in better understanding.

by Nigel M

Sep 18, 2017

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

by Christopher B

Mar 01, 2017

This course was an improvement in teaching modality from the statistical inference course, with more polished content, but the link between the lectures and the actual exercises was still a bit strained. Overall, it felt like there was a bit of a disconnect between the swirl exercises and the lectures, and this led to a lot of self-teaching.

by Samirou T

May 26, 2018

I appreciate coefficients interpretation and variance influence to choose among models.

Running code takes a few seconds, understanding the model's outputs is a much hard

by Pulkit K

Jun 09, 2018

It lacked practical application, not impressed.

by Mingda W

Jun 05, 2018

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

by Andrew W

Apr 05, 2018

Very good at presenting basic concepts. I highly reccomend saving the quiz questions as a good guide as to what you should know. I wish there were more material on generalized linear models.

by Sandro G

Jun 24, 2017

This is the first time that I take a course about regression models. I I found it very useful and enteresting, may be for someone who already know this argument it could be less useful, because in some part it is lacking. I mean above all about some example that could be a little bit more complex than those presented in the videos and that more probably it could be more similar to real cases. In anycase, I would like to thank a lot the teachers and courser for this occasion to learn given to me and others !