返回到 Improving your statistical inferences

4.9

460 个评分

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150 个审阅

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!...

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.

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

筛选依据：

创建者 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.

创建者 Maria A T

•Jun 16, 2017

Excellent course.

创建者 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.

创建者 EDILSON S S O J

•Apr 09, 2018

Nice!

创建者 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!

创建者 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.

创建者 Md. M I C

•Jan 03, 2017

It is good indeed. Such course is needed more on Coursera.

创建者 Amy M

•Nov 03, 2016

Great lectures and really helpful simulations. Very engaging and interesting. Full of useful resources.

创建者 sad d

•Jan 18, 2017

One of the best Coursera courses! Daniel Lakens for the win!

创建者 Iván Z A

•Feb 15, 2017

Wonderful course: very interesting, and very well explained. Also, the teacher is a very kind and helpful person (at least in Twitter ;-P). Thanks Daniël.

创建者 Srinivas K R

•Oct 09, 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.

创建者 Habiba A

•Dec 29, 2016

Easy to follow, light workload, and most importantly: very useful material of supreme importance.

创建者 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!

创建者 Jessi S

•Dec 27, 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!

创建者 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.

创建者 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.

创建者 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!

创建者 Yashar Z

•Oct 17, 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)!

创建者 Zahra A

•Apr 29, 2017

Extremely useful course!

创建者 Sanjeev P

•Nov 13, 2016

Fantastic, enjoyable, entertaining with a dash of humor. Highly recommended for non-statisticians interested in improving their grasp of the field.

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创建者 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.

创建者 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!

创建者 Eva D P

•Jan 23, 2017

Probably the best stats course I've ever taken (and also the most fun and enlightening)!

创建者 Jaroslav G

•Feb 05, 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.

创建者 Aviv E

•Jul 17, 2017

Great course, lots of new tools and materials that really helped me in my study.