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

4.9
stars
751 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

MS

May 13, 2021

Eye opening course. My first introduction to some of the issues surrounding p-values as well as how to better utilize them and what they truly represent. My first introduction to effect sizes as well.

AB

Feb 23, 2020

Easy to follow, well structured, good references, empathy of presenter. I will recomend this to other friends who made Black Belt certification and still don't have clear what the Pvalue is for.

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76 - 100 of 245 Reviews for Improving your statistical inferences

By Jaroslav G

Feb 5, 2018

I found this course very well-structured and easily accessible and understandable even to students, while being highly profound and covering most important and and recent pressing topics in methodology and statistics.

By Srinivas R

Oct 9, 2017

A course taught by a single individual - that packs more learning and knowledge into it than many rote courses. A course that I have returned to and will return to many times in the future to brush up on fundamentals.

By Chandrani S

Sep 10, 2021

Learning through implementation and practice are the best way and this course had a lot of those. The difficulty level was just right and using R programming and Open Science assignment had been a great experience.

By Jonas S

Nov 16, 2016

Very well designed course, from a didactic as well as from an entertainment point of view. I was able to close many gaps in my inferential statistics knowledge and now feel much more confident in my interpretations.

By Rebecca W

Jul 17, 2017

An accessible and interesting course. I learned so much (and refreshed myself on things I should already know!). Thank you so much Dr Lakens for putting together this course. I've been recommending it to everyone!

By Carlos L F

Jul 18, 2017

It's a really interesing course about statistical inferences. You can learn a lot about how to recollect data, how to analyse it and how to interpret it. It is very recommendable for all kind of researchers.

By Mark G

May 9, 2021

This is an excellent course, one which I’d recommend to anybody with an interest in science, or open science, whether you be a scientist or just someone with an interest. Daniel does an excellent job here.

By Mark S

May 14, 2021

Eye opening course. My first introduction to some of the issues surrounding p-values as well as how to better utilize them and what they truly represent. My first introduction to effect sizes as well.

By Aishwar D

Aug 25, 2018

Thank you Daniel Lakens for creating and sharing this course in the way you have done. The content is very appropriate for any one anyone who is looking to work with Inferential Statistics. Many thanks

By Paul

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.

By Alvaro M B

Feb 23, 2020

Easy to follow, well structured, good references, empathy of presenter. I will recomend this to other friends who made Black Belt certification and still don't have clear what the Pvalue is for.

By Victor M

Jul 11, 2021

Solid course which taught me how to interpret p-values in a variety of contexts and taught me to not just to consider but (systematic and practical) ways of how to correct for publication bias.

By Yaron K

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.

By Georgia P

Jun 18, 2021

Really enjoyed this course! The content was perfect to get my stats brain raring to go for my PhD, and now I can go in with a much better insight on interpreting my findings from the get go.

By Andrés C M

Mar 25, 2019

Excellent course. I improved my statistical knowledge and learned more about bayesian inference. Also, I learned something about how to pre-register a research and its benefits of doing so.

By Alvaro B

Mar 23, 2022

Very complete an instructional. This is a very compled topic and concepts stick in your mind through the explanations and materials prepared by Lakens and the exams throghout the course.

By Miroslav R

Feb 22, 2018

Excellent course with a lot to learn. After 10 years in data analysis it provided me with great new insights and material to further improve my skills and understanding of data analysis

By Bob H

Oct 6, 2017

This is a top-notch course. The ground (especially pitfalls) is very well covered, and useful free tools are engaged (R, G*Power, prof's own spreadsheets for calculating effect size).

By Turgon R

Nov 27, 2020

This course is great! I learned a lot about statistics and how to have a critical thinking about tests and results in the literature. I also gain in confidence for doing statistics.

By Tiago Z

Jun 19, 2018

This course changed my concepts not only about statistics but about research and science. Daniel Lakens is a fantastic lecturer and scientist. I can't recommend this course enough.

By Rizqy A Z

Jul 10, 2018

This course is immensely helpful to improve my area of expertise. This course also fills the gap of my previous formal training with current challenges in my career as a scientist

By Yashar Z

Oct 16, 2016

Really nice course! begins from basics but gives you a deeper understanding of concepts. Plus the quizzes are open for auditing (as one expects from an open science advocate)!

By Marcin K

Dec 22, 2016

Great course. Daniel explains everything clearly and with examples in R code which makes all of the concepts easier to understand. A must-take for experimental psychologists.

By Kevin H

May 13, 2019

Very good introduction course. An improvement could be to include more high level summaries of each sections. I think it could help students better organize their thoughts.

By Cesar M

Oct 9, 2022

Excelente curso; es un repaso metodologico completo del análisis de las pruebas estaísticas y que permite un entendimiento práctico de la teoría estadística.

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