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Learner Reviews & Feedback for Inferential Statistical Analysis with Python by University of Michigan

163 ratings
35 reviews

About the Course

In this course, we will explore basic principles behind using data for estimation and for assessing theories. We will analyze both categorical data and quantitative data, starting with one population techniques and expanding to handle comparisons of two populations. We will learn how to construct confidence intervals. We will also use sample data to assess whether or not a theory about the value of a parameter is consistent with the data. A major focus will be on interpreting inferential results appropriately. At the end of each week, learners will apply what they’ve learned using Python within the course environment. During these lab-based sessions, learners will work through tutorials focusing on specific case studies to help solidify the week’s statistical concepts, which will include further deep dives into Python libraries including Statsmodels, Pandas, and Seaborn. This course utilizes the Jupyter Notebook environment within Coursera....

Top reviews


Mar 07, 2019

If you are interested in statistics and statistical analysis, this course gets you grounded in the essential aspects of statistics. Excellent instructors.


Jun 22, 2019

A very in-depth learning material for inferential statistics. Very good explanation of p-value which clarifies some of the prevailing misunderstandings.

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26 - 33 of 33 Reviews for Inferential Statistical Analysis with Python

By Jonas N

Oct 14, 2019

Good Python tutorials that gives a good paratactical introduction to the theoretical core of the course.

By Gabriel G B

Dec 05, 2019

It is absolutely great. Instructors are veeeery pasionated with what they do, and the course material is very good.

I really like this course.

By Frank S Y R

Feb 14, 2019

I really enjoyed the course.

By Yury P

Jul 08, 2019

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

By Kevin K

Oct 29, 2019

Wish there were more practice problems.

By Divyam A

Oct 06, 2019

Some parts can be explained better

By Christine B

Sep 20, 2019

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.

By Darien M

Nov 30, 2019

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