I feel like the course overall was important. I'm glad I have the basic idea of how I can crunch research data using R. However, the course could be difficult and perhaps a bit deep for many people looking toward UX design. The instructor suffers from the academia cliche of having so much knowledge and skill that he can't always help students on a very introductory level. Case in point reading the class notes (a task usually unimportant and ignored by most users) is required, and yet even those notes are written from a perspective of knowledge of the subject. It's a bit like coming into a Spanish 1 class, looking to learn a bit about Spanish and the professor hands you a syllabus of which parts are written in Spanish. While I recovered from this shock, I think for many this snowballs into growing frustration and failure.

Add to this the complexity of coding across different computer operating systems and versions. There are times when you get an error and you don't know why. In a classroom the professor might tell you, "oh you forgot to _______". Here you can ask and you might get a response days or weeks later. It could also get so complex that even the professor is not sure what is going on. I had an error and there was no resolution, I had to google and solve it myself.

Overall, I'm glad I took the course. I had some really painful moments but I also solved problems and completed complex tasks, which felt rewarding. I definitely appreciate the approach of the professor, splitting time between lecture and hands on and having hands on assessment at the end.

It's true that I've learned a lot and will never see experiments the same way again. I have new-found respect for conducting even the most simple surveys. BUT this course goes way too deep into the math and code under the hood. It's absolutely ridiculous. I almost dropped out so many times. I had to invest hours of my scarce time to complete tasks that aren't suited for an Interaction Designer, but rather for a mathematician. I'd rather spend more time analysing results and optimising the design of experiments than figuring what on earth I'm being "explained" about a bunch of intricate formulas. The analysis got completely LOST in that jungle of numbers, weird names and math jargon. Wouldn't recommend.

I've been going through "Interaction Design" courses from University of California, San Diego since course one in order to get the specialisation. And each course was interesting, insightful, challenging. I really want to get the specialisation and I worked hard to get to this point. In total it took me around two years with pauses and breaks.

However, the last course called "Designing, Running, and Analyzing Experiments" is something different and makes it impossible for me and many others to finish. Because it requires programming and statistical skills. So for it to be finished I need to take a separate course on R language. I'm not willing to give up, but this particular course requires special skills which not everyone has. I'm not sure if this R language will be in the capstone project as well but it's just impossible to finish. Moreover, if you go to the discussion forums not only you will see that people can't finish even second week but also that many students can't even install the software that they don't know how to use. I suggest all the R language materials, assignments, quizzes, videos to be removed from this specialisation. Because it requires a special preparation and skills in programming and statistical analysis which this course wasn't meant to require from students.

It's like if I would be doing a course on Microsoft Paint and the last course would be to create a 3D model of a dinosaur in Maya assuming after learning Microsoft Paint we're able to take on the Maya 3D in no time.

I was forced to study something separately just to finish this course. And I'm not planning to use the knowledge from this course. This should be a completely discreet course not related to the specialisation.

This course is not amazing at all. It takes so much time to complete plus you do not learn much. You learn to pretty much replace some parts of a code it's already done in R. So you work with code but you don't learn how to code either. I give this course 1 star.

The worst course of this specialisation. Instead of emphasising on the principles of statistical methods, this course forces you to use R and RStudio.

At first I should thank Dr,Wobbrock for his efforts. He teaches the course materials well but I think the this course is not well-balanced. Statistics is very wide concept and R Studio is big too. Although the course is longer than other courses of this specialization , i dont think it has the same output.

I become familiar with R.

I become familiar with distributions.

I know some of tests but if I want do a real world experiment I dont't know how can i start it now.

I think this course should get redesigned.

I reviewed all previous courses with 5 stars but I had to give 1 star to this course Not because of the instructor and not because of the importance of the material but because of the level it os not well thought through. As a beginner designer information given here without clear explanation of how those studios and softwares work you would be a big problem for anyone who just started getting into this field. Giving us basic skills of using those tools would be more helful rather than asking us to solve problems. I finished all previous courses in less than a month and obtained so many skills and information. I am very frastrated because I was looking forward to finish this specialization.

I liked the professor. He explained things well. My concern with this course it the understanding of it. I can do command line commands but figuring out which commands to use for each quiz question is complicated. The first few weeks I figured out which sections of the coursera.R file to use. Later weeks were more complicated. Perhaps files with commands and comments on a per week basis would be best. Not giving the answers to the student, but at least giving more context per file would be very helpful.

I was enthusiastic about this class but it ended up being useless to me. While the structure allowed me to jump right in R, I felt like without any prior knowledge of statistics, I was just copy pasting without really understanding the tests, and why to use one rather than another. I guess going deeper into what things mean, or adding more context to the tests would help for designers with little background of stats. For example, even though it was explained, it would have been nice that every time we had a new dataset, to take the time to explain what type of survey it was, vs the previous ones, and to map it to the grid. This was assumed as a given, but I feel I would still have trouble figuring out which test to use on my own. So overall this was a good class but missing some content for the beginners.

The instructor and Teaching Aids haven't participated in the learning Forums for over a year- this is the most difficult course in the Specialization however there is little to no support for the students. I have a background in engineering so I faired well in the course, but for many- not so much! Course would also benefit from a more robust intro to R Programming. Thank you so much for the course , I really appreciate it! I'm only sending these criticisms in order to help - I personally did very well in the course.

I'm really sorry to give this rating, but I have no choice. The course was horrendously boring, and so far removed from the interesting and interactive work that we had done in the previous sections of the Specialisation. This is such an unfortunate course to have as a requirement to complete the Specialisation, and especially the final hurdle to get into the Capstone. Moreover it was the longest of all the courses. Thus the least interesting and also the longest - makes little sense!

As I said, I'm sorry to give this rating, but it needs to be said. The teacher seems like a great guy. And I'm sure he's killing it teaching statistics and R Studio at Uni, but using R studio to such a standard just doesn't seem like the everyday work an HCI designer would do. A statistician or data specialist yes, but a UI designer?

Perhaps you could make the course higher level, avoid the indepth R Studio, and make it 3-4 weeks like all of the other courses.

Omigod! You're kicking this off in R-studio and teaching the whole course from this interface? Could you at least use a pen with ink that we can read when you're not in R?!

This might be the last straw for me in this specialization. Nothing about this subject matter is easily digestible for a designer, and I'm okay with that. (I'm also a web/js developer, so I'm used to intense struggles with really abstract stuff.)

What I can't get over is that this is part of an interaction design specialization that teaches design concepts, but whose instructors almost never practice those concepts in their pedagogy. "Do as I say, not as I do" seems to be the prevailing MO. The whole effort seems totally half-baked, and nowhere more so than in this course.

I might not be so harsh if there weren't such great examples of well designed pedagogy elsewhere in Coursera, and for material that's at least as dry as statistics.

Much more emphasis on statistical analysis than on experimental design. Seems out of place with the rest of the specialization in terms of both length and subject matter. Course assessments seem to test in-depth knowledge of coding in R (which isn't gone over in sufficient detail in lectures, rather students are told to look it up in more detail on their own; however, the class is already longer and more in-depth than all the others in the specialization!) more so than experimental design or statistics. Should be less detailed, or split into multiple courses, or at least should have an introductory lesson(s) or prerequisite course on basics of how R works - I found it extremely frustrating trying to learn about and conduct statistical analyses in a system of which I had only minimal working knowledge.

This course assumes too much knowledge about both programming and statistics. The tone of the instructor makes it seem like its an introductory course, but he does not provide an introduction to the concepts and methods that would give the student a proper grounding to successfully advance through the course.

Yes, this is not an intro stats course, and yes, it is not an intro R course. But what is it actually, particularly in terms of UX?

Too technical, with lots of hard concepts to assimilate in a very small time. Exercises are too hard.

A tough course, especially for those who do not code. Thus, lots of work required. Sometimes there were way too many tasks (32). I gave this course 5 stars as it was a very challenging, but lots of different approaches and tests you can learn more and in depth.

This had been the hardest class ever. I don't even know how I passed but also I don't see how I can remember to use Rcode for future work within HCI

As a stand-alone course this would be very good. The presenter is engaging and clearly knowledgeable, and the treatment of the course subject is thorough and well-designed. Grounding UX design in rigorous statistical analysis is important.

BUT as a component of the Interaction Design specialisation it was much too long (nine weeks, as long as the previous three courses combined) and the coursework was un-interesting (long sequences of statistical tests with strange names) and very different to the creative and interactive assignments in the other courses. It very quickly turned into a demoralising "death march" for me.

As part of the specialisation, this course needs to be slimmed-down radically, and perhaps complemented by other analytical approaches to UX and interaction design. In its current form, the inclusion of this course in the Interaction Design specilisation is represents an error of judgement.

This class needs to be structured way differently. There are too many opportunities for error with R Studio. The files should be separated out by weeks and the R file should correspond with each week. It's too difficult on the little viewer to see the code easily. Out of all the courses in this specialization this one was the toughest, mainly because of the organization. I understand there is a lot of detail to the calculations, but students shouldn't be looked down upon because they just don't understand it. The professor is super knowledgeable about the topic, it just was hard to follow along at times. Lastly, estimated quiz time is way off, the required amount of time is much greater.

This was the most arduous undertaking I have ever been through. My frustration is not with professor Wobbrock, who is obviously an expert in his field (though sometimes I felt like he's speaking in "High Valyrian" and not English). My disappointment lies with UCSD which included the course of such depth of information and a strong requirement for understanding R, without much thought on whether students will be able to follow. I feel that going through this course was largely pointless, because I'm not going to retain much of the depth of the material in the long run.

Based solely on this experience, I'm NOT going to be recommending this specialization to anyone.

I think the intention behind including this course was probably well meaning. I think it was a punishing course to get through for those of us who had no background in statistics, scientific studies, or programming. While I was able to fail my way forward through it, it was completely overwhelming, and overly painful. I really think the expectation should be set before students sign on to the specialization, as was I wonder how many students gave up on the whole Interaction Specialization after this course. Prof. Wobbrock was great, but I think there was a lot of vocabulary assumed to be known to us that just wasn't. I felt like I had been dropped down on Mars.

If you do not know R studio or R programming this course will be very difficult for you. The fact that they state you dont need to know this program and then require you to use it to complete tests is unacceptable. Week 2 test onward requires you to modify code or program code in order to get statistics required to answer the questions. Their helpful hints cause errors when used mainly because you must know the correct syntax or placement of the code to get the correct answer.

I'm very disappointed in this class and probably will not pass because I do not have the time to figure out how to program in R.

Neither statistics nor R was covered in any meaningful way. At the end of the course, you are left with frustration for having to jump through the loops, but no understanding of the principles. I am a college instructor for Statistics, having graduated from a PhD program - even with that background I could not follow the instructor.

The course designer never considered the audience, and never identified the goals of this course. The instructor was lost between teaching R and teaching stats, so in the end he did neither. Worst course I have ever taken, both online and face-to-face.

Alunos podem ter dificuldade em baixar o programa. Tive que usar outro computador. Os testes são muito detalhistas e não acho que isso seja um conteúdo adequado para o curso, uma coisa seria ensinar sobre como realizar testes com usuários e técnicas outra é ter a necessidade de usar códigos e contas sendo que um programa de analitísticas mostraria o resultado sem precisar de todo esse esforço.

A terrible course for a beginner in statistics. I cannot believe I have completed the first six courses in this specialization, only to be met by a course that moves so quickly through very complex information, that i will never be able to pass the overall specialization. I am so disappointed. AVOID THIS COURSE. I will be writing to coursera to ask for a refund.