Improving your statistical inferences(으)로 돌아가기

4.9
별점
715개의 평가
236개의 리뷰

## 강좌 소개

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"...

## 최상위 리뷰

MS

2021년 5월 13일

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.

YK

2017년 3월 1일

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.

필터링 기준:

## Improving your statistical inferences의 235개 리뷰 중 26~50

교육 기관: Daniel D

2020년 4월 13일

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.

교육 기관: Jessi S

2017년 12월 27일

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!

교육 기관: Samantha F

2020년 11월 8일

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!

교육 기관: P P

2020년 9월 8일

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.

교육 기관: Rajib C

2020년 7월 5일

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.

교육 기관: Bryan L

2020년 10월 11일

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.

교육 기관: Tory M

2017년 3월 8일

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!

교육 기관: Walter G O

2020년 5월 19일

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.

교육 기관: David

2017년 7월 21일

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.

교육 기관: Ramiro B

2017년 11월 6일

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.

교육 기관: Jan N

2018년 10월 11일

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.

교육 기관: Caroline W

2017년 6월 17일

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.

교육 기관: Zak R

2017년 8월 11일

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!

교육 기관: Joe B

2016년 11월 11일

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.

교육 기관: Vít G

2016년 11월 12일

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!

교육 기관: Sean H

2016년 11월 26일

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.

교육 기관: Mrinalini R

2020년 3월 26일

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!

교육 기관: Michael B

2020년 8월 10일

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.

교육 기관: Oliver C

2017년 12월 17일

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.

교육 기관: Gregory L

2017년 5월 2일

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.

교육 기관: Hollin V

2017년 9월 20일

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.

교육 기관: Matti H

2016년 12월 13일

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 :)

교육 기관: Anisha Z

2018년 1월 6일

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!

교육 기관: Pablo M B

2019년 12월 5일

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!

교육 기관: Kim S

2017년 6월 13일

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!