It would be better to give precise definitions of each test, at least in optional reading material. Also, sometimes different lecturers used different terminologies and sometimes concepts not covered before just popped up in the video (ex. chi-square test). In general, it seems more organization in the material needed.

The course gives details on several stats concepts. Its one of the finest course here on Coursera. You gain a significant amount of knowledge on Statistics.

As the course progressed, I felt the content was squeezed and students were bombarded with the content without giving a real life example on them.

Clear and detailed explanation of inferential statistics. The course approach is more by blackboard than what can be interpreted by the title "with python". Although there are some examples in python, there are not many exercies for the student

Could be made more organized, like the first course in the specialization series. Seems there are some missing gaps (or assumptions of things being covered) that made it a challenge to smoothly proceed in the first 2 weeks of content.

Thank you a lot. For me was an incredible course I learned many things and was very important to my career. Thanks to all the team, They are really masters.

Good theoretical foundation, but lacks explanation on python libraries extensively used in the course.

the fundamentals and intuition are greatly explained. The python part feels a little rushed though.

Great experience, though very helpful and happy working with the real world dataset and problems

A very good one, but it would be great if more challenging exercises and examples were added.

Overall solid course. Could do without peer review assignment, more of a hassle than anything.

i wish there are more (differently structured and defined) datasets to practice in the lab.

Perfect Course, It was very useful to understand the basics of inferential statistics

Good and accessible introduction to hypothesis testing and confidence intervals ...

If you want a course that's 90% statistics and 10% Python, this would be it.

Need Intermediate - Advanced skill level in Python.

good examples expected to have more examples

Need more improvements in engaging students

More mathematic explanations would be nice

Wish there were more practice problems.

Peer Graded Assignments are a joke

very very high level statistic

I really enjoyed the course.

I cant uneroll course

Good one

I had already taken a Statistics course in my College, and took this course less to learn the concepts and more so to understand how to code Inferential Statistic in Python.

I definitely learnt how to do that at the end of the course, Confidence Intervals, Hypothesis testing, Z and T tests, etc. were taught well by the instructors.

However, many of the Lectures don't match the subsequent Quizzes ( quizzes are much easier and sometimes unrelated), and the Jupyter notebooks have you code Normal Multiplication and division of numbers to find the Intervals (for eg), instead of teaching you how to master the Scipy.Stats Module or use other powerful libraries which you will be expected to know if you land a Statistics related role in a Company.

Overall, it was a good course and knowing it's part of a specialization means you still have much to learn, but I hope the course creators make it more challenging for non-beginners and Programmers