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Learner Reviews & Feedback for Inferential Statistics by Duke University

4.8
stars
2,722 ratings

About the Course

This course covers commonly used statistical inference methods for numerical and categorical data. You will learn how to set up and perform hypothesis tests, interpret p-values, and report the results of your analysis in a way that is interpretable for clients or the public. Using numerous data examples, you will learn to report estimates of quantities in a way that expresses the uncertainty of the quantity of interest. You will be guided through installing and using R and RStudio (free statistical software), and will use this software for lab exercises and a final project. The course introduces practical tools for performing data analysis and explores the fundamental concepts necessary to interpret and report results for both categorical and numerical data...

Top reviews

ZC

Aug 23, 2017

This course by Professor Çetinkaya-Rundel is awesome because it is taught in a very clear and vivid way. Lab section and forum are so dope that I love them so much! Definitely strong recommendation!!!

MN

Feb 28, 2017

Great course. If you put in a little effort, you will come out with a lot of new knowledge. I recommend using the book after you have seen the movies. It gives a deeper picture of how it works. Great!

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376 - 400 of 477 Reviews for Inferential Statistics

By Sumedha S

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Jul 1, 2020

Thank you

By manuel e c e

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Oct 27, 2017

Thank you

By EXAL G S

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Feb 16, 2017

Excelente

By Beatriz M A

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Aug 22, 2022

Excelent

By CABANGUNAY , M J (

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Apr 23, 2021

So great

By Alfredo J N

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Feb 10, 2019

Amazing!

By Raj K P

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Sep 18, 2017

good one

By gerardo r g

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Jul 22, 2019

awesome

By guangyuan l

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Aug 2, 2018

amazing

By Jeff G D

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Aug 10, 2016

5-star!

By Lerner Z

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Sep 16, 2020

Great.

By Abdul A

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Apr 7, 2023

well

By Lucia F M D C

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Jul 15, 2021

great

By Praveen S

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Jun 3, 2020

Super

By Charles G

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Jan 20, 2018

Great

By SEBASTIAN L N

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Nov 10, 2024

good

By Prince M R M

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Mar 26, 2024

NONE

By Raphael I F F

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Jul 14, 2023

okay

By Jenard J P P

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Feb 5, 2021

yeah

By Gonzalo C S

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Jul 24, 2016

Cool

By John C L R

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Apr 19, 2021

g

By Sanan I

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Jun 4, 2020

.

By Saravanan V

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Jan 31, 2019

-

By Radoslaw T

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Mar 18, 2018

O

By Emmanuel M

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Aug 18, 2020

Overall a great course. Very rich in material. I do not have a strong math or statistical background and i struggled a bit with the range and quantity of material presented. Hard work is surely involved, but it is ultimately rewarding. A word of caution : if you are taking this course standalone (or as part of Coursera's Data Science Learning Path like me) without taking the first introductory part, you will have to compensate a bit on the programming parts if you are new to R (luckily a lot of freely available instructional material is found on the web, and the professor herself offers a free statistics textbook with online R labs). Not a downside for me, as this course has made me discover this fantastic language which has taken a strong position besides my budding Python skills. Cheers!