The course is designed well. Need more details on Chi-squared and AB testing. Overall it is very informative and helpful. Thank you

If you do not have experience with data analysis (specifically speaking Pearson's chi square technique), you might struggle like me.

Good course. The leactures could be better structured, but with some complementary reading and insistence, you bust right through.

Great, if brief course. Some occasionally ill-worded test questions. But this course piqued my interest for the ones that follow.

Just in week 1, this course has me examining and evaluating things I normally would take for granted...including work arounds!

Overall it was mostly good but the maths was not well enough explained and some of the course materials felt out of date.

Some of the evaluation methods just allow other people how doesn't do to much work to just pass...

A very good learning course. The content could be more in depth to get a better understanding.

The first assignment was very confusing in terms of what was required, and it should be fixed.

Everything is great apart of the third week assignment. I guess it needs to be changed.

Gave basic introduction to design principles but the assignments were very engaging

The course overall was good but the assignment instructions were not clear enough

very good course! the final was much more logical than the first course

This course really helped me understand what to ask of my Design team!

Lectures are clear and extensively cited; assignments are interesting.

Informative course..Thank you professor and coursera.

Good explanation of few design ideas and technics.

Another very good class in this specialization.

Really good introduction to interactive design

good tips for testing experiments

Very interesting course

Interesting materials.

I like it!

This course as much content in it and it's difficult to have an holistic idea how it all fits together. Some videos are taught having the same problem like, for example, some tools/themes are presented without us knowing what they are for. E.g., Chi-squared test and null hypothesis. Only after a while we understand their use. This bring a lot of overhead to us who are learning.

Some videos seem to have been re-worked over time and present cuts or jumps.

As for assignments, they should be better worked because some questions are not clear or misleading regarding the criteria that you want to evaluate.

For example, I already reported that in Question 2. and 3. of the assignment for the 3rd week. The example you give is a short introduction with two problems: 1) "I did the website", which can make the participant not to be at ease to criticize and 2) we're no evaluating the participant performance but the website. Next, you ask us to rewrite the introduction, which we do with those two problems in mind. Now, when we do the peer review we realize that you're expecting for us to rate the new introduction based on having "early prototype" and "user feedback". The original problems just seem not to count. Only by chance you can eventually write the new introduction touching the points that count for grading.

I like the content of the course. I feel I have learned a lot, especially working with the Chi Squared test. However, there was an example that was not clear on week 3 – Comparing rates. The example refers to comparing two buttons in a home page in order to improve traffic. The data provided was confusing because the Instructor refers that 118 people sign up the “learn more” button over a week. He calculates the chi squared value with 118 sign-ups for the “learn more” button. Then he said that 119 people sign up over a week for the same button, and he calculates the chi square value with this data. My suggestion is to review that video. Thank you.