# 學生對 杜克大学 提供的 Linear Regression and Modeling 的評價和反饋

4.7
1,138 個評分
197 條評論

## 課程概述

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....

## 熱門審閱

##### PK

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.

##### VS

Sep 15, 2017

fantastic course on linear regression, concepts are well explained followed by quiz and practical exercises.\n\nthough you need to complete the prior courses to understand this.

## 1 - Linear Regression and Modeling 的 25 個評論（共 195 個）

May 26, 2019

It's a very good course for starting to learn about linear regression. Just be aware that the quality of this course is a bit lower than the previous two. There are fewer videos, the book material is shorter (less suggested exercises and the chapters cover fewer things about linear regression) and some quiz exercises of week 2, which should only cover simple linear regression, have some questions about multiple linear regression which is the 3rd week's topic.

Also, as in the previous two courses, the emphasis is on statistics, not programming with R. This means that if you already know statistics and only want to learn how to use R, there are probably better courses out there for you. But if you want to learn or improve your knowledge of statistics, and also learn how to use R, then do take this course. I think that it's much better to start learning R by actually doing some statistical work and seeing first hand what the software is capable of doing with only a few lines of code, even if you don't fully understand the code's syntax at first.

With all that said, if you take the course PAY ATTENTION TO THE LECTURES, READ THE CHAPTERS and DO THE SUGGESTED EXERCISES. I can't stress this enough. If you don't do all of that, you won't learn as much as you should, and it's painfully obvious that some students didn't do all of that when you review their final R projects. Also, take your time with that final project because that's where you will actually learn some things about R and use what you have learned about statistics (you will have to use google to learn how to code some things properly).

Jan 07, 2019

The course is good regarding concepts and theoretical exercises, but poor regarding applying new knowledge in R. Since the course is introductory, an instruction how to install R and a list of R functions without clear explanation how they should be applied in general regression situations makes me explore other sources to learn how to apply those concepts (e.g. DataCamp, CRAN-RProject, etc) and then get back to learn theory? Sorry for expectations but course should provide a full and integrated package of knowledge and skills, especially for beginners.

Furthermore, no Machine Learning (ML) is covered as a tool to run a regression.

My proposal is to provide an algorithm with a comprehensive example how to run a regression using R. From data to final model, step-by-step.

Sep 22, 2016

Very good course. while it does not cover everything. the teacher does a great job explaining things in a simple manner. My feed back would be to move ANOVA into this module.

Sep 15, 2017

fantastic course on linear regression, concepts are well explained followed by quiz and practical exercises.

though you need to complete the prior courses to understand this.

Feb 05, 2019

Really great course, clear and easy to follow. Highlight recommended.

Mar 15, 2018

The mathematical depth of this course, is insufficient even at its targeted level, and therefore a lot of practical manipulations of the data, and fine tuning of the model could be had if a week more has been put into this course.

Easy does not equate fun, after completing this course, I left the specialization.

Jul 27, 2018

Great instruction on stats, however the R portion a weekly project that is largely self directed, very little instruction.

Jul 01, 2016

Compared to other courses in the specification, this course content is too shallow and brief.

Jun 09, 2016

She just started with wk 2. There should have been more explanation and videos in week 1...not very interesting. I think statistics you need to take in person.

Apr 03, 2019

it provides a superficial knowledge. A deep understanding of subject can not be gain from this course

Sep 13, 2018

Not suitable for beginners

Oct 29, 2018

This course was very challenging. I learn a lot with the model we have to find and it is very interesting to note other students. None of us found the same results. For me, it is very strange not to know at the end what are the good results. It seems that you change the subject overtime. Do you send the correction?

It will be nice to know if we reasoned correctly.

Dec 19, 2017

Great course. The instructor is very clear on the statistical concepts and thorough on the application of various methods. I learned a lot about how to do regression analysis from this course. The R integration is very helpful as well. Overall great course! Everybody should take it and complete all the quizzes and the final project.

Jul 16, 2019

This course was exactly what I needed for a project involving logistic regression. Difficult (way past beginner!) but clear. Doing all the exercises in the workbook cemented my knowledge. Good final project. Very interesting to see other people's results from the final project. Great teacher! Thanks Duke!

Dec 19, 2018

Great course, just like the rest of the specialization.

I am just missing math formality, but I guess that I shall target a different type of course (perhaps even of platform) for that.

Great professor; one can see that besides mastering the material, she has done the homework regarding teaching techniques.

Mar 01, 2017

As with the previous courses on this Specialiazation, the instructor makes the difference. With detailed examples, clear explanations and a very handy supplementary e-book provided for free, this is a must course for everyone wanting to learn Statistics. Highly recommended!

Aug 02, 2017

I truly enjoyed this course. It's one of the most useful and easier to understand than the rest. Could use more samples and information on how to deal with Categorical Data though.

Final Project is a full-time job. 1-week while working full-time is hardly enough time.

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.

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.

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.

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!

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.

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.

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

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.