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学生对 埃因霍温科技大学 提供的 Improving your statistical inferences 的评价和反馈

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196 条评论


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"...



Mar 02, 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.


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.


151 - Improving your statistical inferences 的 175 个评论(共 194 个)

创建者 Jesús D Z M

Jun 12, 2017

very, very great course about inferential statistics

创建者 Bruno V

Feb 19, 2019

Thank you daniel, very educational, I learned a lot

创建者 Peter K

Mar 01, 2019

Excellent course. I learned a lot about inference.


Jun 12, 2020

Un excelente curso guiado por un muy buen maestro

创建者 Reuben A

Apr 17, 2019

The best statistics course I have ever taken

创建者 Leon W

Nov 26, 2016

Great course, much appreciated. Thanks a lot

创建者 Brendan P

Oct 21, 2017

Excellent content and delivery throughout.


Jun 08, 2020

This course is very useful! I recommend.

创建者 Rossella M

Mar 25, 2020

Really useful and interesting course!

创建者 JOHN Q

Jun 04, 2017

Interesting Course. Thanks so much!

创建者 Eleonora N

Jul 17, 2020

Just great. Very insightful course.

创建者 Farid

Mar 12, 2017

Exactly what i needed. But now it

创建者 Maureen M

Mar 21, 2019

The best MOOC in statistis ever!

创建者 Mark K

Jul 10, 2020

This was an exceptional course!

创建者 Pablo B

Sep 22, 2017

Enjoyable, useful, necessary.

创建者 Oana S

Dec 27, 2016

Amazing learning experience

创建者 Maheshwar G

Jun 06, 2020

This is really impactful.

创建者 Zahra A

Apr 29, 2017

Extremely useful course!

创建者 Biju S

Dec 05, 2017

Very interesting course

创建者 Alexander P

Jul 23, 2017

Phenomenal course!

创建者 Maria A T

Jun 16, 2017

Excellent course.

创建者 martin j k

Nov 06, 2017

















创建者 Sarah W

Feb 13, 2020

Thanks Lakens

创建者 Nareg K

Nov 30, 2018

Great course!

创建者 Michiel T

Jul 24, 2018

Great course!