Worth it!

Excellent

很棒 学到很多东西

valuable

Perfect

perfect

Great.

Bests

Great

10/10

good

GOOD

Is

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/

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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.

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'.

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.

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. :)

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.

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.

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.