It would be an excellent course if you have learned R and taken two graduate-level statistic courses in social science; otherwise, it may be hard to finish given the lack in the background knowledge...

One of the best courses I have taken in relation to UX. Very good design, engaging lectures and examples, and well designed exams. I learned alot and enjoyed listening to Dr. Webbrock. Kudos to him.

Great course.

Highly recommended. It was very clear and I'm very thakful because there were many subjects I only understood partially before this course but are now very clear to me.

Very difficult content of the module, but the teacher explained the issues clearly. Tests were also helpful in understanding and mastering the material.

Although the course was claimed that no prior knowledge of R is needed, I reckon that you should equip yourself with fundamentals of statistics and R before joining the course. Initially, I expected to learn more how to design an experiment, but the course turns out mainly teaching running experimental data on R.

This course requires significant knowledge of statistics and coding. It is not a class you can just jump into to learn as a beginner. The teacher doesn't explain anything well - he assumes you already know what he's talking about and he is not helpful in his Discussion Forums often blaming students for not already knowing what he's talking about. This class should not be part of this series.

This course gave me a really solid overview of different statistical techniques and tests and when/ why it is appropriate to apply. It's a pretty basic overview, without much technical detail, but it's exactly what I needed to get me started and help understand some concepts. The explanations are super clear and concise and I'm amazed at how well some concepts are explained, as compared to some other resources. I never leave reviews for anything, but I wanted to sincerely thank the instructors for the work put into teaching this course.

Improve the course: more feedback, more verbal interpretation on the results, and more text on why its Right/Wrong. Learning from Errors, Learning from Feedback is cruicial (Learning Scientists => Bjork, Dunlosky, Metcalfe et al) You should learn a little bit R before. Also knowing something about stats, research methods is also very helpful. I can imagine, that some students without stats background are a little bit lost with this course.

This was really useful. The course was well structured and provided excellent real-life examples that are easily transferrable to other scenarios. Keep it up!

Thrown in to this with little programming background. Sink or swim situation. I swam. It was a challenge and I learned so much!

This was a challenging course for a beginner/novice but definitelyl informative. My rating is largely due to the assessment practices. There were errors in the quizzes, and there was often questions on the quizzes that weren't covered in the lectures - in particular - questions on the week 9 quiz. If you're wanting to "extend" students knowledge, do not do it in marked assessments, rather, do it in assignments and/or practice activities. Utlimately this, along with the higher level of R-Studio knowledge that was expected, were among my biggest frustrations. Content was good, if you know R-Studio a bit, it'll be much easier to manipulate the code/formulas.

I was looking forward to learning [R] Studio. I thought the classes in this course were definitely on the tougher side but for the most part I found the lessons relatively easy to follow if you take notes and I thought the professor's presentation was understandable. It was the quizzes that I take real issue with. Firstly, many of the packages were outdated and I saw numerous comments within the forum about students unable to install or run the packages required for the assessments. Professor Wobrock does mention this in his "readme" doc but that is assuming all students know to read this or to access the forum at all. Additionally, I found that there were many instances when the first quiz for each assessment (covering the concepts) would ask questions about material we had not yet learned. I often flagged this within the coursework when it would appear in the following week's content but there is little sign of any moderator or support for this course since 2019. Additionally, I found that we were being quizzed about a deeper level of interpreting the data than what we actually learned in class. It is one thing to follow along on R while watching the professor do it. There was not enough explanation of WHY we would progress from one line of code to the next, of when to use certain tests or packages over the other. When I did check the forum comments, I noticed professor Wobbrock's tone is rude and condescending. If a majority of students in this course are struggling, that is an issue with the professor, the content, the way the content is being delivered, or all three. It is appalling to me that he repeatedly mentions that the "code is right, the problem must be you" within several of his scant responses on the forum. Lastly, my biggest issue with this course is that we learned how to copy some R code in order to run experiments and analyze data for the specific examples we discussed while following along with the lectures but there was not enough discussion about WHY the lines of code were written the way they were, such as for an interaction plot, this is where the X variable goes, this is where the trace goes etc. Much of the knowledge we are supposed to obtain is possible because of Google. I really object to a professor repeatedly saying "if you want to know more about this, you can Google it." It is not that I even want to know R inside and out, I just want to understand WHY the code is written in the way it was so that I can better replicate the experiments in the future, as well as knowing WHEN to use them. The professor repeatedly says you do not need R experience to take this course but it is my opinion that those who endeavor to complete it would really benefit from beginner knowledge at least OR the materials should be revised to address beginners specifically. I finished this course with a very high average (96%) but I do not feel like I am prepared to use R in a meaningful way. Perhaps I'll "Google it."

This course is targeted towards a very narrow audience who are already highly familiar with R and R coding as well as related stats. It totally alienates other learners who may be coming from non stats/ non-research/ non-coding backgrounds. Given that this course is part of the larger Interaction Design Specialization that is built for all types of learners, this is a huge problem! You can't even unlock the Capstone Project until you successfully complete this 9-week, extremely difficult course. From learning about social computing you are suddenly watching a series of lecture videos where the professor is just running lines and lines of R codes that he previously wrote and talking in stats/R jargon.

They really need to restructure this course ASAP: (1) Spend more time on teaching and explaining the various stats concepts (2) Examples, exercises, quizzes that help us practice how to choose an appropriate experiment design, identify factors/levels and choose an appropriate stats test (3) Consider other stats softwares that are being used in the tech world today that are WAY more user friendly (e.g. Exploratory- that helps simplify and use R). (4) SHOW US HOW TO INTERPRET EXPERIMENT RESULTS AND APPLY THOSE RESULTS TO IMPROVE OUR DESIGN. (5) OR make this course independent and replace it with something that is actually meaningful to this specialization.

You don't need to learn R coding in order to be successful at most design job out there. If you are an amateur in stats, I would just be really cautious going into this course. It is not impossible to complete but I don't think it will improve your understanding or help you be a better designer.

The fact this class states that you do not have to know how to code is ridiculous. It was a cool learning tool to have if it didn't feel so impossible to complete. The instruction videos showing R Studio barely helped teach me as they would just copy and past the code from the file into their demo. We didn't get that option and it felt like I was left to figure most of it out on my own. The file they provide to learn from is also very confusingly ordered and hard to follow. Only getting 2 stars because I see how it /could/ have been an incredibly useful class, but was poorly taught.

It seems like claiming - "this course is not a Physics course" and then teach Einstein's Theory of Relativity in great details. The Statistics, R Programming may be basic for a Math or Stat student but not for most students of this specialization (Interaction Design Specialization). The concenpts discussed are not basic, they go way deeper than needed. I learned math in my college and did two courses on Statistics during my Bachelor's degree. I also have a fair degree of experience in Programming. So I was able to go through it easily. But I can imagine the frustration for learners who do not have these experiences. Other than the experience level required, which is not suitable for this experience, I have a nother major issue. This course discusses in great detail how to get the results using R. But it did not discuss what to make use of the results. This is what should have been the focus and not how you compute the P-Value. Rather you should have talked about what a P-Value is and what we should do with it.

Individually this course is good, I can give it a 4 star may be. But as a part of this specialization (Interaction Design Specialization), it add very little and adds a great deal of frustration for learners.

I'm sure it's a very helpful course for people who specifically need R training or are familiar with statistical computing , but it shouldn't have been part of the Interaction Design specialization. It's extremely complicated, assumes a lot of previous knowledge, and feels hardly applicable or related to the previous courses. It was a complete pain from start to finish, like being back in school in an obscure math class you have zero interest in, especially after completing 6 interesting design courses full of practical assignments. Even the title is misleading as there was nothing about designing, running and analyzing experiments (that actually sounds interesting) - this course is more like 'running data analysis tasks on Rstudio' and that's about it. If we did need some kind of glimpse into this world for the specialization, a simple 'Introduction to Social Statistics' or somethings similar would have gone a long way.

At University we all have that one or two subjects that are unnecessary hard and extremely difficult to pass. These are usually those that we can't seem to see where it would be applied on our careers. Well, here you go, this course is those uni subjects. It took me ages to figure out each quiz, all I could think about is how I'll use this in real life. At the end of the day it's a coding lesson with some copy and paste parts, but overall too hard to understand. I've been working in the HCI field for a couple years now and have never ever seen someone applying this long codes to analyze results. Sorry but this course is for those who want to pursue an academic career and only.

NOT FOR PEOPLE WHO DON'T KNOW R TOOL!

This course needs an interesting approach to keep students wanting to study. The teaching method was boring. The professor was reading things from the screen 90% of the times (he looked bored himself). The topics covered in this course need more time for students to understand 10 weeks are insufficient.

This is the specialisation that sucks all joy out of the entire course. 6 month on and I am still on week 2. The software and the provided files are not fully working, something is always missing, constant error messages... If you don't have background in statistics, you will have a very difficult time.

Overall the videos related to the quizzes are to vague and un detailed, I more often than not feel lost.

Also this should not be part of the interaction design specialisation, and just be a small part of another course.

Not once have I needed R or statistic in my 7 year design career.

The course content is really valuable but the follow up exercises are really difficult to solve on your own. There is not enough explanation given in the lectures by the professor and its really difficult. Some of the answers are incorrect yet no explanation is given.

Disappointed ... very technical course and not so practical for today's world, there is a lot of terms and subjects that you require a good background in statistics analysis to understand well. It is a shame that this take part of the specialization program.

Too much statistics, too much coding and inadequate instruction. This is not a coding specialization and if I wanted to learn coding I would have taken a coding course! This 9 weeks course has been a nightmare!

This was such a frusterating class. Should not have been taken online, or at least give us actual time with someone who knows what they're doing. Felt like it had nothing to do with my actual certificate.

This class was terrible. The homework took significant leaps beyond the in-class exercises, it was hard to follow, and definitely overwhelming for someone without R, programming, or statistics experience.