Great course. The title is speaking and I found what I was looking for.

Great balance between theory (not much) and application (a bit more).

I used different statistical tools in different situation,

everything in R (you mast have a bit of knowledge of it).

Recommended.

This course was put together with lots of thought and care, and I appreciated the thoroughness of the files and assignments. The content was quite dry, and I'm not totally confident in my abilities to execute the tests in real life.

Some times i felt lack of explanation. Because there is a lot of math. And quizzes are too big (10 + 32 questions on Week 7). But overall i would say that this course is the only one to which i will definetly come back

It's a hard course. It's better to have some statistic knowledge. I got a big picture of various methods after finishing this course and I think I need to search for more material to better understand them.

Without any background in R programming and experiment design, I am able to learn a lot of useful stuff in this course. I wish the last three lessons and quizzes are a little more beginner friendly.

This course covers a very wide range of statistical methods but it could use more references to explain in more detail the different tests used. Overall this is a good overview.

Great module but it was very difficult for me as I am a 'non-coder' and R Studio was at times very buggy, so my suggestion is to structure the course differently.

Students need to acquire additional knowledge to really understand the content.

The courses tend to deliver arcane content in a very sketchy way.

I have noticed some of the tests require knowledge that is gained in the next week. I would suggest fixing that.

The instructor for this course was great. He was very responsive to students' questions concerns.

Designing experiments wasn't what I thought, and had a very steep learning curve.

Thank you for designing a course that demonstrates that UX is not just painting!

Great course, a little too long compared to other courses

Very very helpful for my game design project.

Thank you.

More comprehensive than in-depth.

Very analytical and challenging!

It looks great

Although the lecturer has explained many theoretical aspects regarding experiments preparation and analysis well in the course, I honestly don't enjoy this course. The reasons are: 1. this is a stats course to a large extent. So you better have a good understanding of stats using in psychological studies. Otherwise you will GET LOST. 2. This course uses R instead of Python. If you are R novice like me, you WILL HAVE trouble installing packages, modules or using them because of non-compatible version of R etc. The lecturer sometimes will explicitly point out the "right" codes to execute, but it did not work as many other students suggested. Then you asked a question in the forum but unfortunately you still dont get any answer even after you complete this course. In my opinion this also shows poor preparation of the course materials and lack of updating teaching/exercise materials. Copy and paste code seems to become the pattern for completing course exercises, but i really doubt how much you can really apply for real-world cases. With all due respect this course shows a huge contrast with previous course in the interaction design specialisation and really make me feel a bit disappointed.

I have to be honest, I hated this course mostly because I suffered from the start to the end, but don't get me wrong, the concepts are great and very interesting, I didn't know how much information can you get from a simple CSV file; the thing is the course is based in the RStudio tool and I struggled very much with it; missing libraries, constant crashes, and at some point I lost the thread, the concepts start to seem too complex for someone who hasn't much experience with coding so my motivation went away and at the end I was just following instructions to make it through. Maybe if the concepts stay centered on the meaning and not the tool this would be more enjoyable. But I'm very grateful because now I have the sense of data and its importance to backup important design desitions, Thanks!

The content of this course is quite difficult, especially if you are new to R, and there are no moderators or TAs available to respond to questions or discussions about the content. Nobody replies to the students in the discussion forums. This is surprisingly inconsistent with the rest of my experience with the courses in this specialization. I would warn anyone thinking about taking this lengthy course to realize that you will be alone throughout the class and you should be ready to figure things out alone. Also, during Weeks 7-9, the quiz questions don't seem to relate to Prof. Wobbrock's lecture material at all. I took copious notes and that didn't help me identify where the quiz questions came from.

The professor for the course was able to explain well on most of the concepts on the r programming behind the designing, running and analyzing experiments. He went a little fast on the videos but I was able to catch up by reviewing the transcripts and pausing /playing the videos. The part I was not happy about was that there was no mentor in this course who helped out the students on the discussion board in facing issues of setting up r programming and r studio and also understanding how to do r programming. I was a bit surprised that R is used in interactive design because I heard the main programming languages when it comes for UX researchers and designers are focused on java, c++, and sql.

Great intro to R-Studio entering pre-made functions with data tables. I feel a little more familiar with basic concepts for quantitative experiments but in terms of understanding the actual statistical functions I still don't feel confident running know when and where to apply the statistical analysis to the data (Seems out of scope for this one course and I would take this course again for more practice). This was the most difficult course in the specialization. Working in R-studio is tricky because you need to know how run the correct version of R, and how to install missing packages in order to run the functions used in the quizzes.

Interesting to try R hands on. Could have made more definitive statements on the usefulness of each test (there was lots of 'you could have a look at this analysis, or this one, or this one' without covering why each one would be particularly good for this case). Some of the later exercises also made quite of a leap in terms of what you were expected to know about R syntax, although the follow up answers were good if you didn't understand what was expected.

Too technical for my taste. I understood the concepts but as we progressed, the code itself was extremely complicated with A LOT to grasp within a weeks time. I relied on the hints and code keys provided in examinations. I would highlighy recommend either rethinking if code should be part of this. Or improve how we can test/ increase the friendliness. No offence intended, just want to help :)

This module took me on an interesting journey with lots of twists and turns. While I love challenges and learning otherwise I wouldn't have taken this course. I'd like to suggest the following: mentor to assist students, review of codes I found lots of glitches, one quiz rather than two, cut back on timeframe. I'd like to give more stars but am being generous with 3 stars.