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Avis et commentaires pour d'étudiants pour Linear Regression and Modeling par Université Duke

4.7
étoiles
1,590 évaluations

À propos du cours

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....

Meilleurs avis

TM

21 juil. 2020

A great primer on linear regression with labs that help to establish understanding and a project that is focused enough not to be overwhelming, and allows the learner to play around with the concepts

PK

23 mai 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.

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76 - 100 sur 296 Avis pour Linear Regression and Modeling

par Marina C R

19 juil. 2017

Very interesting, I have learned a lot and I have been able to apply it to the final project

par Cosma A

14 févr. 2018

Great work Mine Çetinkaya-Rundel, I liked the wrapping of the course and way of teaching .

par Andrew L

25 mai 2017

Very nice introduction to regression techniques and helpful labs on how to implement in R.

par nguyen h n

25 juil. 2021

I 've only finished the first week. but I like the course because of explanatory examples

par EGAM, A F (

30 avr. 2020

these lessons are great even if the class ends, these are helpful for future assessments

par 詹佳鑫

9 mars 2020

really good course, it will be better if added more R programming learning in the videos

par Shibin T

25 juil. 2017

Very short and concise, and minimal theory related content. Very practical crash course.

par Joseph K

24 janv. 2017

The lessons from this course are very useful, and I will be able to apply them for work.

par Michael O T

20 nov. 2019

It is a course with an excelent level, it is well evaluated and one can to learn a lot.

par Andy D

16 août 2016

Does a good job of explain a complicated topic in a very simple and understandable way

par AULIA A

30 sept. 2020

I'm so very stress but very grateful too and get a lot knowledge. Thankyou coursera!

par Ana M C F

21 août 2020

I really like regression - related topics, and I learned a lot and in an easy way.

par Akshay K

30 juil. 2020

A very good course. I am from the engineering field and this course really helps.

par Alfredo N

28 mars 2019

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

par Jalal A

12 avr. 2018

presenting linear regression concepts is amazing and worth to spend time for it.

par Marina Z

4 juin 2017

Difficult. Possible. Love it. My the most favourite course or the specialization

par Sergio E

21 janv. 2019

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

par anirban d

9 mai 2018

Thanks to the instructor and all the people involved for this wonderful course.

par Alessandro D M

28 janv. 2022

I really liked the way theoretical knowledge is combined with real study cases

par Stephen A

31 déc. 2021

Great introductory course to linear regression. great foundation to build upon

par Arun S

15 juin 2018

Good way to startCovered all basics stuffSimple to understand Good structuring

par Nicholas J

23 avr. 2020

The course material was relevant and well-taught. The course was well-paced.

par Dongliang Z

14 févr. 2020

Excellent Course. Make anyone who is fear staticstics understand Regression.

par Runda Z

7 mars 2021

Really a good course to take, you can learn a lot of things effectively!!!!

par Parab N S

30 sept. 2019

An excellent course by Professor Rundel on Linear Regression and Modelling