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

4.6
stars
763 ratings
138 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

RZ
Apr 1, 2020

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.

RS
Jan 21, 2021

Very good course content and mentors & teachers. The course content was very structured. I learnt a lot from the course and gained skills which will definitely gonna help me in future.

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126 - 135 of 135 Reviews for Inferential Statistical Analysis with Python

By Colby G

Jan 21, 2022

C​ourse focuses more on the mathmatical side without getting too far into much of any programming. I would have liked to have many more labs to go along with what we were learning and have more practice questiosn to solve instead of having my hand held through almost every aspect of the course.

By Aritra G

Jun 6, 2021

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

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 Marnix W

Jan 3, 2020

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

By Divyam A

Oct 6, 2019

Some parts can be explained better

By Andres R d S

Jan 14, 2020

Need to improve slides

By Houtan G J

Jun 24, 2020

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!

By Marangely A

Jan 14, 2021

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

By VENIGALLA N S V J

Jun 6, 2020

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

By Darien M

Nov 29, 2019

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