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

4.6
stars
880 ratings

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.

R

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 - 150 of 160 Reviews for Inferential Statistical Analysis with Python

By Pankaj Z

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May 20, 2020

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.

By Carlos F G

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Feb 21, 2022

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

By Asem K

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Dec 9, 2021

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.

By William O

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Jan 10, 2021

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.

By Yury P

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Jul 8, 2019

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

By Felipe B

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Jan 25, 2020

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

By Harshad S M

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Aug 19, 2020

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

By Faroq A

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Jul 15, 2021

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

By Sam F

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Jan 27, 2020

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

By Zi W

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Feb 14, 2024

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

By Khaled S A

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Mar 23, 2020

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

By Kim J

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Oct 16, 2020

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

By Louise P

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Oct 29, 2022

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

By Bill G

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Feb 24, 2020

Need Intermediate - Advanced skill level in Python.

By k v r

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Apr 21, 2020

good examples expected to have more examples

By syed w a

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Apr 14, 2023

Need more improvements in engaging students

By Nero

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Aug 5, 2022

More mathematic explanations would be nice

By Kevin K

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Oct 29, 2019

Wish there were more practice problems.

By Pankaj K

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May 21, 2020

Peer Graded Assignments are a joke

By Ricardo W E

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Sep 21, 2020

very very high level statistic

By Frank S Y R

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Feb 14, 2019

I really enjoyed the course.

By Feng L

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Sep 5, 2022

I cant uneroll course

By Harshvardhan K

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Oct 14, 2020

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

By Sidclay J d S

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Sep 17, 2020

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.

By Lars K

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Jan 16, 2022

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.