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學生對 埃因霍温科技大学 提供的 Improving your statistical inferences 的評價和反饋

4.9
583 個評分
183 條評論

課程概述

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"...

熱門審閱

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 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.

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101 - Improving your statistical inferences 的 125 個評論(共 184 個)

創建者 Dennis H

Dec 04, 2018

excellent refresher and expansion on frequentists stats (interpretation) and nice intro to bayesian stats. highly recommended.

創建者 Katia D

Feb 11, 2018

Great course! Although I was struggling with lecture 2 (Bayesian Statistics)––It was very mathsy and a bit difficult to follow.

創建者 César A Y B

Feb 26, 2019

Practico sin hacer a un lado lo teorico, te dan un marco mucho mas amplio para la interpretacion y planteamiento de hipotesis

創建者 Agustin E C F

Nov 05, 2019

This is a great course!. It tackles common misbeliefs and approaches the topics both in a technical and coloquial manner.

創建者 Ezra H

May 19, 2020

Very well structured. Every week covered a different important topic. Overall a useful course for empirical researchers.

創建者 唐茂杰

Jan 01, 2020

I think it's a useful course for me, but I think some content in the last week is a little bit trivial for me...

創建者 John B

Jul 17, 2018

very well organised course and deepens understanding. Excellent resources provided also, e.g. books and papers.

創建者 Davide F S

May 21, 2017

Clear, concise, and engaging explanation of many statistical concepts that can be readily applied in research.

創建者 Amy M

Nov 03, 2016

Great lectures and really helpful simulations. Very engaging and interesting. Full of useful resources.

創建者 Lydia A G

May 28, 2020

Highly recommendable course. It puts clarity from the most basic concepts to some other new insights.

創建者 Sandra V

Dec 10, 2016

Extremely useful cours, especially the first 5 weeks! Pleasant and enjoyable. Definitely recommended!

創建者 Fengyuan L

Jul 31, 2020

excellent course. It solves lots of my question over the p value as well as the statistic analysis.

創建者 Habiba A

Dec 29, 2016

Easy to follow, light workload, and most importantly: very useful material of supreme importance.

創建者 Thijs

Aug 14, 2019

Great course. Already had some knowledge about statistics, but this course really improved it.

創建者 Mr. J

Feb 24, 2020

Superbly Done synopsis of statistical gotchas and best practice against them. Very Valauble.

創建者 Morio C

Jan 02, 2020

Great course, clear and helpful. I will definitely recommend it to colleagues and students.

創建者 Jose M S

Jun 17, 2017

Quite interesting and well structured. The contents of this course deserve a wide audience.

創建者 Eva D P

Jan 23, 2017

Probably the best stats course I've ever taken (and also the most fun and enlightening)!

創建者 Sergey L

Jan 01, 2020

The course is full of useful insights and practices. I can definitely recommend it!

創建者 Gerald R

Sep 02, 2017

a very thoughtful introduction to the different approaches of statistical reasoning

創建者 Aviv E

Jul 17, 2017

Great course, lots of new tools and materials that really helped me in my study.

創建者 Richard M

Jan 22, 2019

Great course. A lot of topics introduced and explored. Well worth the time.

創建者 Bertin

Nov 17, 2018

This course is amazing, dynamic and entertaining. Daniel Lakens is brilliant.

創建者 Robert H

Oct 01, 2019

Excellent—an absolute must for all PhD students and early-career researchers

創建者 Shambhavi

Jul 30, 2019

Excellent course, taught well with very useful assignments. Would recommend!