I thought this course did a great job of incorporating R code into the lecture and hope that continues in future courses.

Generally a great course, but would benefit from a better explanation at times of how to use R effectively.

Good videos, good book with exercises but many useful functions in R were not introduced (e.g. t.test()).

More detailed answers on Quiz questions and some more explanation on R codes will help a lot

I think it is a little bit difficult for someone who knows nothing about probability or R.

This course is great learn a lot well explained, the professor is great!!!

Nice introduction to statistical inference concepts and techniques

Very nice coarse for learning methods of inferential statistics.

Very well structured.Could focus on R programming a bit more!

¡Es una pena que no se traten más contenidos! Está genial

Need to revisit few classes as it was little aggressive.

Its a very good way to introduce to R language

good powerful insight into statistics. Thanks!

This is great course as Intro to Statistics

I wish there was more exposure to R.

Very useful tools for inference

It is very difficult...

excellent

excelent

It has skills I need to learn for work using R programming. The instructor for me is hard to follow and squeezes way too much into verbally explaining things in such detail before you comprehend what she has said while at the same time presenting information on the slide incrementally. This leads to me not being able to choose to listen to her or ignore the slide. Maybe you are better at multitasking in real time. With that said you can tell she puts lots of energy into the video and makes things relevant. If you take these courses READ FIRST then watch the videos and be ready to click the pause button so you don't miss a concept that vanishes to the next slide in a few seconds.

I would give it a 3.5, with the extra 0.5 because of the great interaction, ease of use, and clarity of progress. It was pretty hard for me and I barely made it in under the deadline (jumping session to session to complete). You definitely need some R background by the end for the project. I expected to get more in information in using R for inferential statistics too... though there was a presentation and each lesson had followup for use in R. Great use of examples for each section. That helped me a lot.

The fundamental concepts of statistics are well explained, however the exercises involvig R are kinda rushed up. Moreover, the R part is accomplished mainly by a library, dplyr, and the main concepts of R as a programming language are skipped. Finally, the peer grade review is a little more advanced than the course lessons and takes really a painful process - but this is a common problem in coursera.

For me there is not much more than u could learn in comparison to previous course. Would expect some more knowledge from this course

great instruction on statistics, but no lectures on R. The R portion of the class is given as a lab at the end of each week.

The lady could have used a bit more rehearsing before recording.