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

Statistics theory is well explained with several examples and additional resources, lectures are very clear, but it is part of a Statistics with Python Specialization, I expected to have more deep instructions about statistical part of Python (packages and strategies), there are lots of questions about Python coding and functions into the forums, I think a lecture explaining the different packages and functions would be a good idea. From my point of view the Python tutorials could also be more explored, it was too much on surface of it for me.

Mistake in the course instructions and very redundant material. A better understanding of the concepts rather than a series of walk-throughs for different scenarios, would've been better suited to me. Recommended external resources were good. Overall, an ok course, but definitely not the best in terms of design.

This is a very great course. Statistics by itself is a very powerful tool for solving real world problems. Combine it with the knowledge of Python, there no limit to what you can achieve. But this course is quite difficult , but interesting also

I found Brady T West's videos in Week 4 to be unnecessarily confusing causing me to have to go back to Week 3 lectures to clarify the steps of hypothesis testing.

I'd like a little more interaction with Python during the explaination itself.

Some parts can be explained better

Need to improve slides

I guess I managed to learn some coding tricks with Pandas in this course, but I'm not sure what else it was supposed to teach. To the extent that I learned any statistics concepts, it was by searching on google to try to find explanations of whatever the instructors were talking about. They seem to have no interest in explaining anything, to be honest. They throw various equations at you without any indication of where these equations come from or why they work. Sometimes very important points, such as degrees of freedom in a test, are only mentioned as an aside. Really felt like a waste of my time and money. Hopefully there are some better statistics courses out there.

I will never take another course from University of Michigan. I'll just finish this specialization because I went 2/3 of the way and I feel bad if I don't get the certificate. but it was such a wate of time, one of the worst courses I have ever taken. it is not hard, it is bad! I don't recommend this to anyone because there is nothing to learn, unless you want to watch 12 weeks course to learn how to plot and read csv files and multiply numbers in python!

It was irrelevant and contained unnecessary content. Why are we drowning in theoretical statistical topics instead of focusing on Python? Thus far, the course has been more about statistics than actually working with Python! I am here to address my statistical needs using Python, not to become an expert in statistics. Unfortunately, this course seems to be doing just the opposite.

Peer reviewed things should be eliminated. It's taking forever to rate an assignment, in fact, more than the "expected date" that they show.

My final specialization course certificate not received, even after completing all courses in this specialization.

Python does not deserve to be in the title of this course.