Retour à Linear Regression and Modeling

4.7

936 notes

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168 avis

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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par 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.

par 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).

par 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.

par Anukul

•Apr 03, 2019

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

par Richard M

•Feb 05, 2019

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

par Syed S R

•Sep 13, 2018

Not suitable for beginners

par Mark N

•Jul 27, 2018

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

par 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.

par Sherrod B

•Jul 16, 2019

This course was exactly what I needed for a project involving logistic regression. Difficult (way past beginner!) but clear. Doing all the exercises in the workbook cemented my knowledge. Good final project. Very interesting to see other people's results from the final project. Great teacher! Thanks Duke!

par gerardo r g

•Jul 10, 2019

Excellent

par Naivadhya

•Jun 30, 2019

not so good

par Heungbak C

•Jun 06, 2019

Good lectures!

I learned many thing from this course!

Thanks

par Natalie R

•Jun 03, 2019

Clearly presented. R instruction is pretty minimal, so there is a lot of trial and error and googling.

par schlies

•May 31, 2019

Good videos and projects

par Jacob T

•May 29, 2019

Incredible course with interesting projects and excellent explanation.

par Guillermo U O G

•May 12, 2019

I liked, but I guess it could improve little by including more topics in linear regression analysis.

par Lalu P L

•Apr 22, 2019

Could be more informative

par FangYiWang

•Apr 19, 2019

A good course for Bayesian statistics.

par Alfredo J N

•Mar 29, 2019

Excellent. A well designed course and the explanation are very easy to understand

par Henri M

•Mar 22, 2019

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

par GUO S

•Mar 19, 2019

Nice module! It is very clear.

par Aleix D

•Mar 03, 2019

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

par Olga

•Jan 27, 2019

Great course!

par Sergio E T

•Jan 22, 2019

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

par YASHKUMAR R T

•Jan 16, 2019

Simple syllabus, but excellent explanation.

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