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

4.9
460 ratings
150 reviews

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 10.000 learners have enrolled so far!...

Top reviews

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.

MR

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

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76 - 100 of 149 Reviews for Improving your statistical inferences

By Jinhao C

Jun 24, 2018

A must-take!

By David

Jul 21, 2017

Great, well designed course. By far the best online course I've taken on any platform for any topic. In my opinion the course offers something for all experience levels and is useful as a first advanced excursion into statistics for beginners, but equally interesting as a refresher for experienced researchers. Thanks to Daniel Lakens and everyone else who was involved into making this course possible.

By Michiel T

Jul 24, 2018

Great course!

By Joe B

Nov 11, 2016

This course was great. I have worked with statistics for a while but always grappled with some concepts. Having completed this course, I feel much more confident in interpreting findings and designing studies. This is especially the case for Bayesian statistics and likelihoods that were not even part of the curriculum when I went to university.

By Mathew L

Jun 04, 2017

One of the best courses I've ever done. Fundamentally practical. I learned a great deal and challenged a lot of my implicit assumptions.

By Leon W

Nov 26, 2016

Great course, much appreciated. Thanks a lot

By Tory M

Mar 08, 2017

This course was very helpful indeed. My insight into these areas of statistics is now better than it was before, and it wasn't even a terribly painful experience! It was refreshing to have statistical concepts explained so clearly and - dare I say - sensibly. I have already recommended this course to several colleagues and will keep doing so. Thank you very much for putting together such a high-quality course!

By Oliver C

Dec 17, 2017

A really important course for anyone who wishes to make statistical inferences as part of their research. I highly recommend this for people at all stages in their career - particularly for people currently planning their research. It is very well delivered and will make you question your statistical knowledge.

By Michael E

Jun 25, 2017

Thank you. This course represents a great deal of important work for me to continue to revisit and incorporate in my efforts moving forward.

By Zak R

Aug 11, 2017

A brilliantly informative and engaging exploration of some the issues involved in data analysis and hypothesis testing. Though I'm probably still a while away from using many of the techniques covered myself in formal research, I certainly feel better equipped to interpret existing research and spot potential statistical slip-ups. Much recommended!

By Jesús D Z M

Jun 12, 2017

very, very great course about inferential statistics

By Constantin Y P

May 17, 2017

Great course for getting to know heterodox statistical paradigms, how open science could improve the scientific endeavor as a whole, the reasons that led to the replication crisis in some scientific areas and how to correct them. Due to this course I feel more confident analyzing scientific papers, meta-analysis and study designs. It also gave me great tools for conducting my own research, like getting to know the TIER protocol and the pre-registration process. This course awakened my interest in philosophy of science to a degree that I will start a second master´s degree in history and philosophy of science next semester. Prof. Lakens is excellent at making complex issues simple to understand, his videos are entertaining, informative and very well thought out.

By Muhammad T S

Nov 09, 2017

This is a very powerful course. Simple content but with lots of depth and newer perspective on statistical testing. Learned a lot. Highly recommended.

By Jose M S

Jun 17, 2017

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

By Heidi M

Dec 30, 2016

fun and very informative course - thank you very much!

By Mesionis I

Jun 06, 2017

Excellent course!!!!!!Really descriptive with great examples and practises!!

By Nicholas J

Jan 23, 2018

One of the most valuable MOOC experiences I have ever encountered. Thank you, Dr. Lakens for creating such a worthwhile course! (Note that the course assignments are time-consuming, but they are well-designed and demonstrate concepts well.)

I have a PhD in Economics and wish this MOOC opportunity was available during my first year as a graduate student. It would have helped me immensely. Moreover, I wish that the leadership and members of the lab I used to work for would have also taken this course or at least not superficially accept the core principles of the open science culture that were demonstrated in this course. It would have minimized the bad research practices that were going on there!

By Moos L

Nov 06, 2016

Excellent, may I say indispensable course for every social scientist out there to improve their statistical skills. Very coherent and comprehensive!

By Gregory D

Mar 27, 2018

Excellent course. Must take for any students interested in doing scientific research, especially in the domain of the social sciences. Very interesting and informative.

By Oana S

Dec 27, 2016

Amazing learning experience

By Maria A T

Jun 16, 2017

Excellent course.

By Sean H

Nov 27, 2016

I'm so glad I took this class! I learned how to better design experiments and interpret common statistical practices in the literature. The lectures are entertaining and informative, and the professor is charming and funny. Even though I'm an immunologist and the course is aimed at the social sciences, I feel like a better scientist now.

By Răzvan J

May 30, 2017

This was a very usefull learning experience. It helped me to understand better at a conceptual level many statistical methods that are not taught very throughtly in formal education (e.g., Bayesian inference, equivalence testing etc). However, the biggest gains come from the many practical exercises at the end of each module. As a suggestion, in Week 8 I think there should be an additional recapitulation/practice quiz that should consist in more practical exercises (e.g., calculating likelihoods or posterior probabilities, effect sizes etc). Now week 8 (the practice quiz and the final exam) tests the content almost exclusively at a conceptual level.

By EDILSON S S O J

Apr 09, 2018

Nice!

By Jakob W

Jan 05, 2018

Hi! Thanks a ton for a spectacular course. I pick up new understanding every week here, and I actually look forward to going through the material each week. So great job!