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Voltar para Linear Regression and Modeling

Comentários e feedback de alunos de Linear Regression and Modeling da instituição Universidade Duke

4.7
estrelas
1,520 classificações
281 avaliações

Sobre o curso

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....

Melhores avaliações

TM
21 de Jul de 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 de Mai de 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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226 — 250 de 277 Avaliações para o Linear Regression and Modeling

por Richard N B A

9 de Nov de 2016

Great introduction to linear regression. Nice, clean R tutorials via the labs. The lectures do become a little monotonous, but there there are linked readings in a nice, open-source textbook if reading suits you better than listening.

por Tomasz J

15 de Out de 2017

Very good and gentle introduction to linear regression. The final assignment however uses dataset which is very risky to use with linear regression (not all conditions were met in all the assignments I rated!). This is confusing.

por Aditya V

26 de Abr de 2020

A great course on regression. Though some topics weren't taught in the lecture but they can be easily covered using the links provided in the course. Additionally, a more detailed lecture on diagnostics plot can be useful.

por Amara Z

6 de Dez de 2020

A very practical course with hands on sessions in regression. I loved the final project which actually helped me to apply everything that I learnt during the 4 week period and hence cleared so many doubts I had in mind.

por Jennifer g e

12 de Jan de 2021

i would like it very much if the course had more auxiliar videos about R code, because is maybe the most dificult thing to follow on the course. In general the course is amazing, very well explained, i learned a lot.

por Duane S

30 de Mar de 2017

This course provides a very good introduction to basic linear regression, including simple multiple linear regression, model building and interpretation, model diagnostics, and application in R.

por Erik B

26 de Fev de 2017

Good, but a little "smaller" than the Inferential statistics course (which is very complete). I would have liked to also learn Logistics regression, which I now have to learn elsewhere.

por Allah D N

12 de Dez de 2018

Files for this course were broken and I faced a lot of trouble to find good one. This course may be made more comprehensive and not assuming that reader have also understanding.

por Roel M

18 de Dez de 2020

A nice experience, clear explanations, lots of exercises that are really important. The project also allowed one to reflect carefully on how to use R to carry out the analysis.

por Charles G

20 de Jan de 2018

Good but I felt some gaps in the material made it difficult to learn. Also, the quiz questions are focused on attention to detail "gotcha" questions. This can be frustrating.

por Aydar A

20 de Dez de 2017

Nice course. The downside is that it only explains interpretation of linear regression, but not enough details about how linear regression is performed from math point of view.

por Jessye M

13 de Jan de 2017

This course was good. However, compared to the other courses in the specialisation had less content. I would have liked to have videos on logistic regression as well.

por 冯允鹏

27 de Nov de 2016

Compared to the Course 2 Statistic inference, this session seems to be a little be informal and rush. But still learn a lot from the conception of linear regression!

por christian a

25 de Abr de 2018

Really good course as the previous ones in this specialization. Could have included something more on checking for collinearity with categorical variables.

por Dgo D

30 de Mar de 2017

It was a really good introduction to Linear Model, I recommend this course to all people who wants to learn more about statistical analysis

por Ana C

30 de Out de 2016

Excellent Course. Mine, the teacher is a great great teacher. The mentors help a lot.

Technical parts, coursera platform should work better

por Janice H

5 de Jun de 2020

Lecture explanations are fantastic as are slides. Pace is appropriate. R information is a little sketchy but manageable with diligence.

por Nathan H

19 de Dez de 2018

Very informative for an introduction. Wish it was longer and more mathematical, but there are other courses on Coursera for that.

por Tony G

29 de Jan de 2017

Good overview of regression modeling. Would have liked to see more on logistic regression. But that's ok, can read it on my own.

por Scott T

9 de Ago de 2016

Great course. I only wish there was more time spent on dealing with more complex situations such as overfitting.

por Shivani J

5 de Abr de 2020

I liked the course. I learnt a lot while working on its project. Instructor's way of teaching is very engaging.

por Elham L

7 de Abr de 2020

The material in this course is explained very well. However it requires one has the knowledge in using R.

por Siyao G

6 de Ago de 2019

Contents are easier compared with other courses in this series. Quite systematic and easy to understand.

por Natalie R

3 de Jun de 2019

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

por Guillermo U O G

12 de Mai de 2019

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