Retour à Regression Modeling in Practice

4.4

237 notes

•

48 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

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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 bourges

•Mar 02, 2017

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

par MANOJ K

•Feb 22, 2016

Awesome course. Thanks Prof. I am expecting more courses.

par Rahul K

•Nov 23, 2015

This is the only course on SAS(structured) available for free till date

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 Dina I

•Nov 03, 2017

It needs hard work and a lot of practicing :)

par David W

•Mar 15, 2016

Great but too much stock video footage of people smoking.

par ngoduyvu

•Feb 16, 2016

v

par Ruben D S P

•Jun 29, 2018

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

par Sergio A G G

•Mar 29, 2016

I really like this training. It's good if you want a good view of applied regression.

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 kwangje.baeg

•Jan 09, 2017

Background Sound is awesome haha

par Roland K

•Feb 08, 2016

I would do it again, even if there was no tutor support in discussion forums it teaches the arguments very good.

par Vijai K S

•Dec 11, 2015

I enjoy this course so far. I like how the course entirely depends on peer grading. It will help us to get some honest feedback on our research.

par Monika K

•Apr 22, 2016

I think you will get a lot out of this course/specialisation if you don't expect to be spoon-fed. I have seen comments here stating that only one dataset is used per course, not covering all the other options available. This is because you are supposed to understand the concepts presented to you and apply them to your own set and ideas.

The same in terms of grading: you should know whether your code throws up mistakes, how to fix those and whether your conclusions make sense.

It's preparation for the real world: the onus is on you to seek alternative sources of help at time (like stackflow), to correct your mistakes, to understand whether the result makes sense. Your classmates are only there to keep you to the deadline. In real life no-one will hold your hand.

Concepts are explained very well, I am finding it easy to complete two courses simultaneously quite quickly. Great specialisation.

par Bruno R B

•Nov 21, 2016

Excelente curso!

par Arnold A

•Jun 09, 2016

Again, great job!

par Jinbo C

•Jan 08, 2017

easy to follow

par Zacharias P

•Jan 20, 2016

Very nice lecture videos and explanations! Totally worth it

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 Robertas P

•Jun 28, 2019

I liked the course. I would recommend it to others. Do not have any complains. However, I recommend you to consider making the grading procedure more granular, and providing an example sketch of how the exercise reports may look.

par Ponciano R

•Jan 21, 2019

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

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 Ali R

•Jul 30, 2016

simple and useful

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