I have no statistics background so I'm struggling to make any sense out of this course. I wish I could skip it but it is mandatory to proceed to capstone project of the specialization.

There are lots of issues with different version of R and the compatibility with some packages. Especially Mac users can't finish specific tasks.

not helpful , extremely difficult for non programming background people , out of context of the course , bad teaching material and approach

No coding experience, nothing I'd ever use in a working environment. Cancelling course as this is far too technical!

Not recommended. Not clear why we need to use R and learn all this statistics. Not practical for use in UX design.

Little to no use for me. Should not be included in the specialization... I didn't sign up for a data class...

Needed to much knowledge of the R language and has little to do with design

This has been the most frustrating experience of my digital life.

Too much theory less practical things.

It is rather intense (which means - very informative) course and I enjoyed it very much. It helped me understand the principles of the experimental design, how to read data analysis reports and the logic behind statistical analysis techniques.

I've read many negative reviews before starting the course and was very nervous at first. But even without any programming background, it was possible to follow the instructions and complete the coding tasks for me. In any case, the course doesn't require you to code, but mostly copy-paste the provided code and insert new values. You just need to slightly understand what is what in R studio.

All of that being said, I want to add big thanks to the tutor - Jacob Wobbrock. You managed to evoke curiosity towards statistical analysis in me - something I've never expected to happen :D Now I am eager to explore more in this field.

Amazing class. Covers a great deal of statistical methods and explains them in a plain/clear/accessible way with good examples.

It cuts through the chase and gives you what you need to know (the real essentials) from a practical standpoint. You will not get a lot of theory (for that, there are plenty additional courses) but you will get enough theory to select the right method for each scenario.

It will not teach you to program in R from zero (for that there are many other courses) but it will jump start you with snippets of code that you can read, understand, modify, and use.

Real useful stuff... done the proper way...

I could immediatly implement the concepts and instruments provided in this course to my professional activity. I must say that I have a poor training in statistics and a superficial knowledge of R, but I needed to implement more professional usertests (I'm an instructional designer with a background on education).

I really enjoyed the clear explanations; above all, how the concepts where linked to R practice, which was thrilling to me.

Thanks to the team! Great course!

Juliana

I've taken a few stats courses many years ago. I wanted a good overview of how to do a range of statistical tests within R and an introduction to GLM, LMM and GLMM. This course really fit the bill for me. It is also helpful in sorting through the huge "ocean" of R packages to figure out a useful subset that work together. The sample code provided by the instructor is an EXTREMELY valuable starting point.

This course was extremely helpful in understanding which statistical test to use when, with applications specifically for interaction design, which is what I need :) I appreciated the clear relationship between the lectures and the quizzes & assignments. The lectures also were clear. The course was broken up into doable chunks that made it easy to take while still having a full-time job.

That course was going to drive me mad but it's one of the most useful parts of the specialization. I already know where to use it in my job as most people listen to numbers more. I think that the problems that appeared in the process of calculating the results are some bugs in R and have nothing to do with the design of the course. Good job, Jacob and Scott! You're great, guys!

Great course on experimental design providing a detailed overview of running and interpreting factorial ANOVAs beyond the 'standard' t-test and chi-squared test. Given that the bulk of the assessment is based on analysis of experiment data in the R programming environment , I can see why this course may be challenging for those without programming or statistical knowledge.

Excellent course. Very well organised. Challenging yet satisfying. Jacob Wobbrock is a very good tutor and despite the complex nature of the course material, he is engaging and thorough in his approach but leaving just enough for the student to explore and practice on their own. Very enjoyable. Thanks

This course was an deep dive into data analytics and designing experiments for analytics. Although there was a great requirement to perform the tests by yourself - which i guess some designers don't appreciate - it still was an exciting and challenging experience!

Great course! Very applied and less theoretical which is great in understanding how to analyze experiments without getting too deep into the theory. Would love a follow up course that dives deeper into the mechanics of the functions used in this course!

It's a great course. It is very well structured and provides a foundation of research and I am glad that it is a part of Interaction Design specialization. However, might be extremely challenging for people without Statistics experience.

A challenging but very fruitful course.

If you do not have sufficient statistics background, you will find it much more challenging and need to pay much effort on it.

Having said that, you can learn a lot of practical and useful concepts.

This is a thorough course, but was way harder than I expected. I needed to understand the experiment design more than to learn R programming language. I am glad I did, but it was hard for me and took a lot more effort than anticipated.

Excelente curso. Todos lo temas fueron explicados muy bien. Los comando R muy prácticos. Ejemplos reales. Lo único que me gustaría es que presentaran un libro para profundizar en los conceptos estadísticos y ejemplos prácticos.

A very complete tour of methods for analyzing experimental results using R. Its more about practice than theory, but it filled in crucial gaps in my knowledge and I expect what I learned will be very valuable moving forward.

Great course, easy to comprehend various tests/models and their usage! Definitely recommend to anyone running A/B tests. Would be nice to have a short video on which tests are related to multivariate testing.