Linear Regression and Modeling に戻る

4.7

1,043件の評価

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181件のレビュー

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....

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.

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by Jessye M

•Jan 13, 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.

by Daniel C

•Apr 20, 2017

Very useful insights and lea

by Ana C

•Oct 30, 2016

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

Technical parts, coursera platform should work better

by Richard N B A

•Nov 09, 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.

by zhenyue z

•Jun 07, 2016

nice lecture, but it is really too short, not into too much details.

by Sean T

•Jul 04, 2018

Really enjoyed this course! It teaches you the theory you need to understand how a linear regression model works, how to check that your model fulfils certain conditions so that it is valid, and how to build and implement your model in practice!

by Charles G

•Jan 20, 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.

by Saif U K

•Jul 20, 2016

An extremely good introductory course. A must for undergraduates. The style of teaching is fluid and you learn concepts step by step. For more advanced learners the only drawback I see is that this is, by default, an introductory course.But still for advanced learners it can be a great (and I really mean great) refresher.

by Ananda R

•Mar 14, 2018

excellent

by Neeraj P

•Feb 08, 2017

First, this course will enable me to understand the quantitative part of a research. Additionally, this will help a student to understand the essence of performing such numerical calculations and will make us understand the relationship between different variables.

Secondly, this is the need of the hour and such numerical functions are used worldwide so, learning this course will help in almost every field be it 'Management' be it 'Social Sciences' or be it 'Human Behaviour'.

by Dgo D

•Mar 30, 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

by Amir Z

•Sep 01, 2016

This is a great course for this specialization but don't expect much depth.

by Scott T

•Aug 09, 2016

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

by Tony G

•Jan 29, 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.

by Erik B

•Feb 26, 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.

by FangYiWang

•Apr 19, 2019

A good course for Bayesian statistics.

by Lalu P L

•Apr 22, 2019

Could be more informative

by Guillermo U O G

•May 12, 2019

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

by Siyao G

•Aug 06, 2019

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

by Natalie R

•Jun 03, 2019

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

by Veliko D

•Oct 20, 2019

The course is good and the material is presented clearly. The capstone project is very good and makes you really use all the knowledge obtained in the course and the pre-prequisite course Inferral Statistics. My only dissatisfaction is that the course was rather short: only 3 weeks of material and 1 capstone. Therefor it covered less material then I expected. For example, I expected logistic regression to be covered.

by Kshitij T

•Nov 03, 2017

Only contains linear regression as opposed to other model types

by Brandon F

•Oct 16, 2017

Provides a good overview, but I felt some loose ends were not addressed in terms of how stringent the conditions need to be met, and if one can use MLR when this is not the case.

by Micah H

•Apr 30, 2018

Other nits about the depth and breadth of the course aside, I thought it was a good course. The main critique I have to offer is the lack of emphasis of using the power of R. When teaching model selection, the course should have at least provided instruction—or at least a written resource—on how to write the R code for automating forward/backward selection by R^2.* Being a course about using R as well as about linear regression and modeling, it seems like the appropriate thing to do.

(*A classmate whose final project I peer-reviewed used for loops to run the forward model selection based on R^2. That's how I learned about it.)

by Zhao L

•Aug 09, 2016

Covers the basic of Linear Regression, would like to see more advanced material.