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
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 Lou B V•
創建者 Eduardo M•
創建者 ADITYA W P•
創建者 Md N I S•
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創建者 Maurizio S•
創建者 Byeong-eok K•
創建者 RAHMA M F•
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創建者 Musthafa B E•
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創建者 Sanan I•
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創建者 Walter V•
The key concepts of linear regression are explain really well, without heavy mathematical explanation, that is good, because the main concepts are what it important.
The project at the end of the course is REALLY good, you can learn a lot from the analysis and investigation you need to do on it, it took me around 30 hours to really understand and complete (a full time job of 1 week), which is really nice.
I give 4 stars to the course, because they don't dig very much in variables selection, specially with categorical variables, with are the ones i had an hard time during the project. Note: It was hard, because it was difficult, but in the process i learnt a lot of things investigating.
Besides this point, the course is really good to say: "I know the basics of linear regression, I know how to handle it in R", the topic of "Linear Regression and Modeling" is of course much, much more larger than what can be explained in 1 course.
創建者 Neeraj P•
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'.
創建者 Veliko D•
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.
創建者 Jason L•
Awesome course with very clear material! I do wish that the course had a bit broader of a scope (i.e. also covering logistic regression and other kinds of regression with non-numerical response variables). Compared to the Inferential Statistics course, it feels like there was a bit less material. Otherwise, I was very happy with this course. :)
創建者 Saif U K•
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.
創建者 Artur A B•
The material is very straightforward and gives a great introduction to multiple linear regression. My only reservation is the length of the course, which seems to be a bit shorter than other courses in the certification. Would love to have more material/in-depth exposure to components available to us in R.
創建者 Albert H•
It's a nice overview of linear regression but I feel like there needs to be more time spent on model selection processes, collinearity/confounding/intermediate variables, and interaction terms. It's super important for accurate model building for research purposes.
創建者 Aaradhya G•
Again, Dr. Mine Cetinkaya Rundel is amazing. However, linear regression is a vast topic, and maybe another week could have been better. But nonetheless, the concepts explained herein are crystal clear, succinct, and taught in an engaging manner.
創建者 Sean T•
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!