Linear Regression and Modeling に戻る

4.7

1,018件の評価

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178件のレビュー

This course introduces simple and multiple linear regression models. These models allow you to assess the relationship between variables in a data set and a continuous response variable. Is there a relationship between the physical attractiveness of a professor and their student evaluation scores? Can we predict the test score for a child based on certain characteristics of his or her mother? In this course, you will learn the fundamental theory behind linear regression and, through data examples, learn to fit, examine, and utilize regression models to examine relationships between multiple variables, using the free statistical software R and RStudio....

May 24, 2017

Very good course taught by Dr. Mine who is as always a very good teacher. The videos are very eloquent and easy to understand. Highly recommend it if you are looking for a basic refresher course.

May 25, 2019

I feel I'm running out of complement words for this course series. In conclusion, clear teaching, helpful project, and knowledgeable classmates that I can learn from through final project.

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by Mindaugas Z

•Jan 07, 2019

The course is good regarding concepts and theoretical exercises, but poor regarding applying new knowledge in R. Since the course is introductory, an instruction how to install R and a list of R functions without clear explanation how they should be applied in general regression situations makes me explore other sources to learn how to apply those concepts (e.g. DataCamp, CRAN-RProject, etc) and then get back to learn theory? Sorry for expectations but course should provide a full and integrated package of knowledge and skills, especially for beginners.

Furthermore, no Machine Learning (ML) is covered as a tool to run a regression.

My proposal is to provide an algorithm with a comprehensive example how to run a regression using R. From data to final model, step-by-step.

by Richard M

•Feb 05, 2019

Really great course, clear and easy to follow. Highlight recommended.

by Rui Z

•May 25, 2019

I feel I'm running out of complement words for this course series. In conclusion, clear teaching, helpful project, and knowledgeable classmates that I can learn from through final project.

by Diego R G

•May 26, 2019

It's a very good course for starting to learn about linear regression. Just be aware that the quality of this course is a bit lower than the previous two. There are fewer videos, the book material is shorter (less suggested exercises and the chapters cover fewer things about linear regression) and some quiz exercises of week 2, which should only cover simple linear regression, have some questions about multiple linear regression which is the 3rd week's topic.

Also, as in the previous two courses, the emphasis is on statistics, not programming with R. This means that if you already know statistics and only want to learn how to use R, there are probably better courses out there for you. But if you want to learn or improve your knowledge of statistics, and also learn how to use R, then do take this course. I think that it's much better to start learning R by actually doing some statistical work and seeing first hand what the software is capable of doing with only a few lines of code, even if you don't fully understand the code's syntax at first.

With all that said, if you take the course PAY ATTENTION TO THE LECTURES, READ THE CHAPTERS and DO THE SUGGESTED EXERCISES. I can't stress this enough. If you don't do all of that, you won't learn as much as you should, and it's painfully obvious that some students didn't do all of that when you review their final R projects. Also, take your time with that final project because that's where you will actually learn some things about R and use what you have learned about statistics (you will have to use google to learn how to code some things properly).

by Mark N

•Jul 27, 2018

Great instruction on stats, however the R portion a weekly project that is largely self directed, very little instruction.

by Anukul

•Apr 03, 2019

it provides a superficial knowledge. A deep understanding of subject can not be gain from this course

by M. I F

•Jun 09, 2016

She just started with wk 2. There should have been more explanation and videos in week 1...not very interesting. I think statistics you need to take in person.

by Syed S R

•Sep 13, 2018

Not suitable for beginners

by Dario B

•Dec 19, 2018

Great course, just like the rest of the specialization.

I am just missing math formality, but I guess that I shall target a different type of course (perhaps even of platform) for that.

Great professor; one can see that besides mastering the material, she has done the homework regarding teaching techniques.

by Charles C

•Dec 22, 2018

The course provides good insights for linear regression. Also, I think the professors are intended to statistics and its application in real life.

by Tulio R C

•Dec 11, 2018

Amazing content!

by Olga

•Jan 27, 2019

Great course!

by Gencay I

•Jan 03, 2019

10/10

by Pedro G F M

•Nov 22, 2018

Great course! as a suggestion I Believe Duke should publish new courses on other prediction tools (like SVM, for example)

by Robert

•Nov 23, 2018

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by Abdullatif A

•Nov 24, 2018

The flow of information is clear and understandable.

by Jaime R

•Nov 08, 2018

Very useful and practical

by YASHKUMAR R T

•Jan 16, 2019

Simple syllabus, but excellent explanation.

by Daniel C J

•Jan 07, 2019

A great intro to linear regression, both from theoretical and practical point of view. Really enjoyed the course!

by PRIYANKA D

•Jan 08, 2019

Exceptionally helpful for beginners due to perfect combination of theoretical and practical sessions.

by Sergio E T

•Jan 22, 2019

The applications of linear regression models are vast. This is a useful course.

by Aleix D

•Mar 03, 2019

Very good, and most important of all, very well explained!

by GUO S

•Mar 19, 2019

Nice module! It is very clear.

by Henri M

•Mar 22, 2019

Great contents and great teacher. I enjoyed it very much.

by Janio A M

•Aug 04, 2018

Great work! Really intuitive and helpful for regression cases.