Retour à Regression Modeling in Practice

4.3

234 notes

•

47 avis

This course focuses on one of the most important tools in your data analysis arsenal: regression analysis. Using either SAS or Python, you will begin with linear regression and then learn how to adapt when two variables do not present a clear linear relationship. You will examine multiple predictors of your outcome and be able to identify confounding variables, which can tell a more compelling story about your results. You will learn the assumptions underlying regression analysis, how to interpret regression coefficients, and how to use regression diagnostic plots and other tools to evaluate the quality of your regression model. Throughout the course, you will share with others the regression models you have developed and the stories they tell you....

Mar 07, 2017

Awesome course. More than regression generation, they have explained in details about how to interpret regression coefficients and results and how to make conclusions. 5 Stars

Nov 28, 2016

This was a great course. I've done a few in the area of stats, regression and machine learning now and the Wesleyan ones are the most well-rounded of all of them

Filtrer par :

par Enyang W

•Mar 19, 2019

The course itself was nice, but the review for the assignments was really annoying, I always had to wait sooo many days..

par Ponciano R

•Jan 21, 2019

Good course with a lot of applicable techniques. Thanks for your time and teachings!

par Mukkesh G

•Jan 14, 2019

This course is really an eye opener. I had no idea statistics would be this much fun! The way the course is set up is just beautiful. Concepts are clearly explained, and they give you such a good insight into the world of data science. Definitely gonna recommend this to a lot of people

par Aurimas D

•Jan 07, 2019

unbalance course. in my opinion simple topics were over-explained and difficult topics were under-explained. I personally would prefer to know more about regression in the first place and only then try to adapt them to the data. perhaps it my lack of knowledge.

par Ruben D S P

•Jun 29, 2018

Great classes. You need all of the content to manage data.

par Γεώργιος Κ

•Jun 22, 2018

Many useful and must to know things. I am not satisfied by the explanations to difficult tasks that need further understanding and deepness. Anyway I am glad to have taken that course, it offered knowledge to me. In fact I recommend it to those that have heard of regression and need supportive material.

par Dina I

•Nov 03, 2017

It needs hard work and a lot of practicing :)

par Amin F

•Aug 08, 2017

This specialization was great up to this course! All the content are reviewed superficially and it seems the instructors are just trying to teach recipes and there is no intuitive explanations, especially on multiple regression and the tests for evaluating it.

par Aneeshaa S C

•Jul 31, 2017

course could've had more depth. expected explanation on more data scenarios. for example, logistic regression when the explanatory variables are quantitative.

even interpretation of output. course is too brief. barely gives you an introduction to the subject.

par Glenn B

•Jun 07, 2017

really enjoyed it

par Gopisankar M G

•Apr 02, 2017

great course , a must for all science students

par bourges

•Mar 02, 2017

Very clear and documented videos, ability to choose between two différents statistical software: python and sas

par kwangje.baeg

•Jan 09, 2017

Background Sound is awesome haha

par Jinbo C

•Jan 08, 2017

easy to follow

par Meigui Y

•Dec 05, 2016

This is a great beginner level course for those have no programming experience. But I would suggest the content to be extended to 8 weeks instead of 4 weeks.

par Paul C

•Nov 28, 2016

This was a great course. I've done a few in the area of stats, regression and machine learning now and the Wesleyan ones are the most well-rounded of all of them

par Bruno R B

•Nov 21, 2016

Excelente curso!

par 晏文丹

•Oct 01, 2016

The course content is very well-designed and to be honest, it doesn't go very deep into the statistical details and i completed the whole course within just a week. Still, it lays a good groundwork for future studies. Don't expect to be a data specialist after this course, but it definitely teaches you all the basic knowledge(Multiple regression, Logistic regression, examine model fit using q-q plot, standardized residuals and multiple diagnostic plots) you can start to implement to analyze your own data. And of course, if you are interested in all these topics and want to expand your knowledge, this course prepares you to furthure your studies. Great course! And I will sure recommend it to my friends with or without a statistical back ground.

par Ricardo M

•Sep 26, 2016

Assignmetns allow student to choose dataset and analysis - but are not very well structured.

Detailed exaplanations.

par Abdullah A M A

•Aug 16, 2016

great effort was paid preparing this course .

par Ali R

•Jul 30, 2016

simple and useful

par Victoria

•Jun 26, 2016

Extremely boring and not

par Arnold A

•Jun 09, 2016

Again, great job!

par Nitin K

•May 30, 2016

Good Course. To the point and clean lectures.

par Jason M

•May 21, 2016

Similar to other courses in this specialization, the material is very nice (although slightly easy and straightforward), but the course instructors do not moderate the discussions enough to make them a useful tool. Especially when I'm paying for the specialization, I would appreciate responses to my questions.

Coursera propose un accès universel à la meilleure formation au monde,
en partenariat avec des universités et des organisations du plus haut niveau, pour proposer des cours en ligne.