A good course for Bayesian statistics.

Great model with clear explanations

Nice overview and R examples!

Very useful insights and lea

Could be more informative

Awesome course.

A good course

excellent

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.)

Overall it covers everything that you would want this course to.

However, I was a complete beginner when starting this course, and as a result I regularly got confused (especially when it came to coding in R)

3/5 stars for me

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.

lectures are great.

but no tutor answers my question posted in discussion board.

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

Only contains linear regression as opposed to other model types

The grading is just so annoying

dropped

Average

The course required no prerequisites, but no one can complete the course without actually completing the courses preceding this in the specializing series.

not so good