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Learner Reviews & Feedback for Improving your statistical inferences by Eindhoven University of Technology

4.9
stars
791 ratings

About the Course

This course aims to help you to draw better statistical inferences from empirical research. First, we will discuss how to correctly interpret p-values, effect sizes, confidence intervals, Bayes Factors, and likelihood ratios, and how these statistics answer different questions you might be interested in. Then, you will learn how to design experiments where the false positive rate is controlled, and how to decide upon the sample size for your study, for example in order to achieve high statistical power. Subsequently, you will learn how to interpret evidence in the scientific literature given widespread publication bias, for example by learning about p-curve analysis. Finally, we will talk about how to do philosophy of science, theory construction, and cumulative science, including how to perform replication studies, why and how to pre-register your experiment, and how to share your results following Open Science principles. In practical, hands on assignments, you will learn how to simulate t-tests to learn which p-values you can expect, calculate likelihood ratio's and get an introduction the binomial Bayesian statistics, and learn about the positive predictive value which expresses the probability published research findings are true. We will experience the problems with optional stopping and learn how to prevent these problems by using sequential analyses. You will calculate effect sizes, see how confidence intervals work through simulations, and practice doing a-priori power analyses. Finally, you will learn how to examine whether the null hypothesis is true using equivalence testing and Bayesian statistics, and how to pre-register a study, and share your data on the Open Science Framework. All videos now have Chinese subtitles. More than 30.000 learners have enrolled so far! If you enjoyed this course, I can recommend following it up with me new course "Improving Your Statistical Questions"...

Top reviews

PP

Jun 29, 2020

Excellent explanations. Strong examples. Helpful exercises. Highly recommended for anyone who ever has to conduct inferential statistics or read anything that reports a p value or bayes factor.

YK

Mar 2, 2017

Excellent course. The lecturer has written code snippets that let the students visualize the meaning and interrelationship of p-values confidence-intervals power effect-size bayesian-inference.

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201 - 225 of 260 Reviews for Improving your statistical inferences

By Jesús D Z M

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Jun 12, 2017

very, very great course about inferential statistics

By Bruno V

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Feb 19, 2019

Thank you daniel, very educational, I learned a lot

By Peter K

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Mar 1, 2019

Excellent course. I learned a lot about inference.

By CRISTIAN C L V

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Jun 12, 2020

Un excelente curso guiado por un muy buen maestro

By YiÄŸit A

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Dec 3, 2024

Great course to improve inferential statistics.

By Max M

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Apr 25, 2023

The best course I did so far. I learned a lot.

By Miruš J

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Nov 20, 2020

The most useful statical course I took so far.

By Reuben A

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Apr 17, 2019

The best statistics course I have ever taken

By Leon W

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Nov 26, 2016

Great course, much appreciated. Thanks a lot

By Brendan P

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Oct 21, 2017

Excellent content and delivery throughout.

By Siméon C

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Dec 6, 2020

It was just great ! Thank you very much !

By MASCIANTONIO

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Jun 8, 2020

This course is very useful! I recommend.

By Juan F

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Oct 17, 2024

Excellent, engaging and really useful!

By Rossella M

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Mar 25, 2020

Really useful and interesting course!

By JOHN Q

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Jun 4, 2017

Interesting Course. Thanks so much!

By JUNAID A

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Jun 29, 2021

One of the best courses on Coursera.

By Eleonora N

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Jul 17, 2020

Just great. Very insightful course.

By Farid

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Mar 12, 2017

Exactly what i needed. But now it

By Maureen M

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Mar 21, 2019

The best MOOC in statistis ever!

By David S

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Feb 15, 2021

Great content and lab document.

By Mark K

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Jul 10, 2020

This was an exceptional course!

By Wenkai S

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Feb 17, 2022

Very informative and helpful!

By Pablo B

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Sep 22, 2017

Enjoyable, useful, necessary.

By Janssen

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Oct 17, 2024

Clear and excellent course.

By Oana S

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Dec 27, 2016

Amazing learning experience