13 de mai de 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.
10 de jul de 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.
por Daniel D•
13 de abr de 2020
Going through this course really solidified my understanding of many concepts, going from "I have an idea of what that is." to "I understand that!" ;-) The additional references (papers, videos) added a lot. The R script assignments were not dificult and very informative. It was also good to be exposed to other online s/w available, including the research support sites like AsPredicted and OSF. Lakens' presentations are well done and engaging. A very good course.
por Jessi S•
27 de dez de 2017
This has been one of the BEST courses I have taken (including other online course and my university courses). The course has definitely increased my understanding of making statistical inferences and has also provided me with hand tools and exercise. The professor used a variety of tactics to engage learning (reading, assignments, video, websites, quizzes) and all of these helped me to learn. It was a very engaging course with very useful information. THANK YOU!
por Samantha F•
8 de nov de 2020
Clear, multimodal teaching/e-learning with examples and hands-on practice in R with code and visualisations. I really enjoyed this course and would recommend this course to anyone who is learning about, and using statistics and statistical inferences in their research involving quantitative methods. This course was given in a friendly and supportive tone and made learning 'scary' statistics a thing to look forward to. Thank you Daniel Lakens!
por P P•
8 de set de 2020
Excellent course. The rigor that has gone into the video's and downloadable materials is remarkable. The tests and quizzes are thought provoking and the amount of code in R for various lessons is in itself worth way more than the 49 for the course. Anyone who is interested in statistical inferences and wants to understand more about effect size, power, significance level etc and see it applied in practical terms should take this course.
por Rajib C•
5 de jul de 2020
I am so glad that i enrolled and completed this course. It is an excellently designed course and offer us an understanding on how critical decisions on inferential statistics are, which is definitely not taught in universities. For a Ph.D. scholar like me, enrolling and completing this course could not have come at a more better time than this. And finally a big thank you to our Course instructor. He is an amazing teacher. God bless.
por Bryan L•
11 de out de 2020
I think this course is exceptional for its target audience. I am just a guy trying to learning a bit more stats, and while I thought this course would be a good introduction to me (and it was!), it also relied on a lot of concepts I should have known before I started, especially the whole idea of statistical tests. I still learned a lot. I think the instructor should include a better description of pre-requisites on the course page.
por Tory M•
8 de mar de 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!
por Walter G O•
19 de mai de 2020
Un muy buen curso para mejorar la interpretación de los análisis estadísticos.Además incluye una gran cantidad de ejercicios con uso de variados software de código abierto que permiten mejorar las habilidades para el calculo de distintos test estadísticos. En los últimos capítulos se complementa con una muy buena formación en filosofía de las ciencias, y las buenas tendencias para construir ciencia abierta.
21 de jul de 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.
por Ramiro B•
6 de nov de 2017
I really like this class, it was very useful and the content was high quality. My only issue - which might have nothing to do with the class or the instructor - was that the exams were really long and boring. It would have been more enjoyable to be to have shorter, more focused examinations instead of a long exam at the end of a section or at the end of the class. EdX does this better.
por Jan N•
11 de out de 2018
Nicely packed body of information necessary to understand your data and to infer any judgements about real world impact of scientific research. The course led me to question my way of creating inferences about my research and conclusions of others. Now, I can be more precise in formulating hypotheses and interpreting results in the way that is closer to truth. Thank you.
por Caroline W•
17 de jun de 2017
I thought this was an excellent and enjoyable course. Daniel Simons is a great teacher, and I learned a lot as well as picking up some practical tools for the future, such as easy to use spreadsheets to calculate and convert effect sizes, and confidence intervals. I'm an R novice, but got on fine with it and really appreciated the pedagogical value of the R-simulations.
por Zak R•
11 de ago de 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!
por Joe B•
11 de nov de 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.
por Vít G•
12 de nov de 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!
por Sean H•
26 de nov de 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.
por Mrinalini R•
26 de mar de 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!
por Michael B•
10 de ago de 2020
Very interesting look at statistical inference. So much emphasis is place on P-values in reviewing studies, but not enough emphasis on the limitations of P-values as indicators of study results. This course provided some cautions regarding study results and some different ways of looking at results to draw supportable inferences.
por Oliver C•
17 de dez de 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.
por Gregory L•
2 de mai de 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.
por Hollin V•
20 de set de 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.
por Matti H•
13 de dez de 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 :)
por Anisha Z•
6 de jan de 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!
por Pablo M B•
5 de dez de 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!
por Kim S•
13 de jun de 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!