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.
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
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.
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.