返回到 Linear Regression and Modeling

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1,342 個評分

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237 條評論

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....

Jul 22, 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

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.

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創建者 Chris A D

•Oct 12, 2019

This course explains the statistical aspects of linear regression. A detailed explanation of minute aspects of linear regressions. The quizzes and assignments are quite exciting. Recommend to anyone with little know (4/10) knowledge regarding Linear Regression.

創建者 Valeriy K

•Dec 19, 2019

Another fantastic course by Duke staff. I'd love to thank Professor Cetinkaya-Rundel for the passion that she shares. I really loved working on weekly labs and a final project. I learned a lot of tools and developed my own functions while solving the tasks.

創建者 Cynthia J J

•Aug 09, 2020

This was a challenging but very rewarding course. I feel that my analyst skills have greatly improved as a result of understanding and applying the ideas through the quizzes and final project. Thank you very much to the instructors!

創建者 Zhou C

•Jan 19, 2018

A good course introducing basic ideas in linear regression and modeling! However, it might be better if future versions of this course could include slightly more advanced concepts such interaction and logistic regression model.

創建者 Arnold T

•Oct 26, 2016

This is the first course that's made me understand linear regression. The instructor is so spot on, and all areas are covered including diagnostics which I find most teachings skipping. Awesome course!

創建者 Tanika M

•Jul 22, 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

創建者 Praneeth K

•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.

創建者 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.

創建者 Long D H

•May 15, 2020

It has been a great adventure so far. I still greatly appreciate how final projects are constructed that gives us freedom to choose our approach to the problems within the data set.

創建者 hou

•Jul 16, 2020

This course was designed fabulously! However, you'd better have some statistics skills before this class, like EDA and programming skills, since the final project is sooooo hard!

創建者 Yaw O

•Jan 02, 2017

Again like the first two courses, this course was great. The Lectures were excellent and the assignments very helpful in solidifying understanding. Thanks a lot Dr Mine

創建者 Julian A S

•Nov 04, 2018

I enjoyed this course. It was quick, but I learned a lot! I thought the assignments were well-thought-out, and the custom R package for the course was a nice touch.

創建者 Marcus S

•Jun 21, 2018

This was the first course where I started noticing that I'm really learning and was able to apply some of the earned knowledge at work.Totally recommended.

創建者 Amanda B

•Nov 28, 2017

Great course! I've already taken a similar stats course using SPSS and this course was an excellent refresher, while increasing my familiarity with R.

創建者 Lucía M F

•May 12, 2020

Very complete course, although it would be nice to include some explanation about the interaction between variables in a multiple linear regression.

創建者 Hao.Xue

•Jul 04, 2017

wonderful module! easy to understand. the labs are extremely helpful which enables you to have a good command of practicing linear regression with R

創建者 Charles C

•Dec 22, 2018

The course provides good insights for linear regression. Also, I think the professors are intended to statistics and its application in real life.

創建者 Ashutosh S

•May 01, 2020

It is a very nice course. The instructor's way of delivering the content is flawless and very precise. The course has been designed very nicely.

創建者 Hanyue Z

•Oct 02, 2016

The structure of this course is really good. The slides demonstrates everything clearly. The speed that the instructor talks is good too.

創建者 Bruno R S

•Jan 20, 2018

One of the most useful of the series, can be valuable as a standalone course on Regression and Correlation. It is also very accessible.

創建者 David W

•Jun 06, 2017

The Professor is a clear communicator and has a flair for finding interesting and engaging examples to illustrate the concepts.

創建者 Amarendra S

•Apr 23, 2020

Excellent course, wonderfully organised and in-depth yet simplistic explanation technique makes understanding regression easy.

創建者 Shao Y ( H

•Nov 27, 2017

Nice course. Comparing this course with the second and fourth ones in the specialization, this is a rather light-weighted one.

創建者 Andrea P

•Mar 21, 2018

Very interesting course and well taught!! Advice to everybody also if you have not much previous experience with regression.

創建者 Pedro G F M

•Nov 22, 2018

Great course! as a suggestion I Believe Duke should publish new courses on other prediction tools (like SVM, for example)