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

4.9
stars
507 ratings
165 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 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

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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26 - 50 of 164 Reviews for Improving your statistical inferences

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 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 Vít G

Nov 12, 2016

Dear Daniel,Let me thank you for this marvel of yours. Your course helped me to revise and to (re)structure previously learned issues, it enriched me with new contexts that were presented in a truly enjoyable way, and last but not least, it gave me completely new insights including the role of simulations in teaching.Many thanks for your work!

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 Mrinalini R

Mar 26, 2020

excellent course for any one interested in learning about statistics, biostatistics and data analysis. I am personally a little fearful of mathematics but this clurse is very easy to follow, the lecturer has a fantastic way of teaching and the assignments are so beautifully designed, that i have printed copies of all of them. Must do!

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 Gregory L

May 02, 2017

Great course! Goes over proper statistical inference and its interpretation from multiple perspectives. The hands-on R exercises are invaluable. Don't be scared off by them - you don't really need to know R to do them. If you interpret literature from the psychological or medical fields, this is a great resource.

By Hollin V

Sep 20, 2017

Concepts are explained in an easy-to-understand way with a good use of analogies. Homework assignments are straightforward and useful. I like the way he teaches using simulations. He encourages students to play around with his simulations to discover how changes in the simulations' inputs affect the results.

By Matti H

Dec 13, 2016

I encourage all my friends in research to not do anything before doing this course! The pedagogical touch is different to any stats classes I've been on or stats MOOCs I've taken. After many lectures, I was just left staring at the screen, with the phrase "I must tell everyone" repeating in my head :)

By Anisha Z

Jan 07, 2018

Probably the most useful course I have ever taken. I think this is essential for anyone who does science. It provides a clear understanding of inferential statistics while discussing common pitfalls and myths surrounding p-values and confidence intervals. Assignments were very useful. Highly recommended!

By Pablo M B

Dec 05, 2019

This is one of the best courses I've ever taken. Professor Lakens has found the key points to be communicated and the key way to communicate them. He has put a lot of work here, and provides very good explanations, very useful practices, nice R scripts and other very good resources. Thank you very much!

By Kim S

Jun 13, 2017

An excellent course that provides a good introduction into the various statistical methods. I have definitely learned a lot of very useful information that I know I will use a lot in the future. I would really like to see a follow-on course on Bayesian Statistics now that I have got a taste for it!

By Emmanuel D

Apr 10, 2018

A real pleasure to take this course ! The videos are extremely pleasant to watch and give away a lot of knowledge, without ever having this feeling of getting lost ! The assignments are fair and extremely useful as well as the exams ! Will definitely recommend (and actually already have ! =P)

By Georgios P

Jun 25, 2018

An intermediate course, which will grant new knowledge to everyone who is interested in making better inferences. It also needs a great deal of studying from external sources for all those who encounter these topics i.e. Type I error inflation, for the first time!

By Benjamin F

Aug 16, 2018

Taking this course was the best decision of the start of my grad school. It has massively improved my ability to interpret other papers and plan my own experiments, as well as changing how I view psychology/science in general. Plus Daniel is a great teacher :)

By Pavol K

Aug 16, 2017

Amazing course. Definitely worth to accomplish. Highly recommended for every researcher, lecturer, PhD. student or student that is interested in prestent state of art regarding choosen important topics statistics and methodology, especially in Psychology.

By Anna S K

Mar 22, 2018

Great course with practical examples and exercises! Clearly explains typical statistical misunderstandings and provides tips for a responsible and honest scientific practice. I really enjoyed it and already recommended it to all of my colleagues.

By Ryan M

Sep 07, 2019

This course was fantastic. I believe I learned more in this class than I learned in three formal behavioral statistics courses. I highly recommend this course to other grad students, and I look forward to the next course that Lakens is creating!

By Jose J P N

Oct 09, 2018

A great course to learn or refresh theoretical concepts behind statistical inferences. There is also a lot of hands-on material and additional content. I think I will come back to the videos and slides when I want to refresh some concepts.

By Nic B

Jul 17, 2017

This is an excellent course for firming up statistical knowledge and replicable research practices. Likely useful for all psych/cognitive science PhD students and researchers further along who come from the frequentist training tradition.

By Tim B

Jan 05, 2017

This was a really well presented course, giving a fantastic overview of inferential statistics and always presented with a sense of humour! A number of really useful tools where introduced which I will be using again and again.

By Martine K

Jun 21, 2018

Really great course! Was already familiar in statistics, but learned a lot about making inferences based on statistical tests. Lectures and assignments are very clear. Would recommend it to everyone interested in statistics.

By Esthelle E

Jan 23, 2019

It was truly an awesome course! I learned a lot from the very well done videos, and well thought-through assignment. Would recommend to anyone trying to marry theory and application in ways that are actually helpful! BRAVO!

By Max K

Nov 28, 2019

This course will actually improve your statistical inferences. It's helpful to get an overview and better understanding of different statistical approaches and a nice introduction into Baysian stats. Would do it again!

By Meghana J

Oct 17, 2019

The course is well-structured and excellently taught. The content is well researched and presented. The assignments are very practical and educative. (The philosophical references in the course content were on point!)