返回到 Improving your statistical inferences

4.9

470 个评分

•

154 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 LIU Y

•Mar 22, 2017

Very good!!! I like this course and the hair style of the professor. ^_^

创建者 Mario R

•Apr 10, 2017

Great course! Everybody doing human/social science should do it!

创建者 Farhan N

•May 21, 2018

I found out about this course as i stumbled across Professor Daniel's blog one day and i feel very lucky that i did. Chances are, like me, you are making some very common mistakes in using and interpreting statistics which is why this course is a MUST for anyone in a discipline that uses statistics and i wholeheartedly recommend it to anyone who has taken a few introductory courses on the subject, regardless of their level of expertise.

The instructor goes through very real and practical topics in the use of statistics and weaves it with adequate theory, examples through simulations, exercises and plenty of additional sources. Common mistakes are highlighted and very useful solutions/tips are provided. The level of difficulty is very accessible and there is not much mathematics beyond algebra and basic probability, although you can go more in depth into technical supplementary readings, should you choose to do so. The instructor also replied to queries and helped out where he could. There is also a really good corresponding (although independent) facebook group on methodology that is very informative and from which i learn new things everyday.

This course is one of the main reasons i am now learning more mathematics so i can properly use statistics in my field of study (Psychology) and i would like to thank professor Daniel for making such a wonderful, eye opening resource for everyone who uses statistics.

Enroll as soon as you can!

创建者 Leon W

•Nov 26, 2016

Great course, much appreciated. Thanks a lot

创建者 Miroslav R

•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

创建者 JOHN Q

•Jun 04, 2017

Interesting Course. Thanks so much!

创建者 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!

创建者 Glenn

•Jun 21, 2017

Excellent course. The materials were well laid out and explained in an accessible but thorough manner. I've already begun using what I've learned in my current work.

创建者 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.

创建者 侯静波

•Jun 13, 2018

very good course! The teaching style is good and the assignment in R is very helpful for me to understand the main ideas of this course.

创建者 Marcin K

•Dec 22, 2016

Great course. Daniel explains everything clearly and with examples in R code which makes all of the concepts easier to understand. A must-take for experimental psychologists.

创建者 Carlos L F

•Jul 18, 2017

It's a really interesing course about statistical inferences. You can learn a lot about how to recollect data, how to analyse it and how to interpret it. It is very recommendable for all kind of researchers.

创建者 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.

创建者 Danielle L

•Aug 29, 2018

An excellent, informative, organized course. Highly recommended!

创建者 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 :)

创建者 Oaní d S d C

•Aug 17, 2018

The course taught me a lot about data analysis and the philosophy of science. By focusing on the processes associated to doing science (data collection, theory generation, statistical inference) the course prepares you to design studies and think better about any area of research (it`s all data after all). But not just that, it made me rethink various things I do in life. I have to say that while, and now after, doing it I started to take a more scientific and data driven approach to all problems in my life. 10/10

创建者 Michiel T

•Jul 24, 2018

Great course!

创建者 Helén L

•Aug 17, 2018

The course was great for refreshing my understanding of statistical inferences. Additionally, it provides an easy to understand introduction to bayesian thinking. The apps and websites, as well as the R-codes and excel-sheets provided alongside the assignments, and the lecture videos are of high quality and proof of a thorough and intesive preparation of the material. The material is very helpful, both for learners and for those teaching statistics to students. Plus, Professor Lakens lectures are entertaining and fun to watch.

I really enjoyed the course and have already recommended it to my department.

创建者 John B

•Jul 17, 2018

very well organised course and deepens understanding. Excellent resources provided also, e.g. books and papers.

创建者 Rizqy A Z

•Jul 10, 2018

This course is immensely helpful to improve my area of expertise. This course also fills the gap of my previous formal training with current challenges in my career as a scientist

创建者 Reuben A

•Apr 17, 2019

The best statistics course I have ever taken

创建者 Nicholas

•Apr 28, 2019

Fantastic course on inference, difference between frequentist and Bayesian concepts like p-values, confidence and credible intervals, and validity.

创建者 Andrés C M

•Mar 25, 2019

Excellent course. I improved my statistical knowledge and learned more about bayesian inference. Also, I learned something about how to pre-register a research and its benefits of doing so.

创建者 Kevin H

•May 13, 2019

Very good introduction course. An improvement could be to include more high level summaries of each sections. I think it could help students better organize their thoughts.

创建者 Andreas K

•Jul 15, 2019

While the course is for researchers, also non-researchers like myself can get a better understanding for methods and pitfalls in science. You need to have prior knowledge of basic statistics and how to perform statistical tests, such as a t-test. I read up on the latter on the Internet, which proved sufficient.

Most examples are from psychology, but the principles are general. In this brief course, very little mathematics is used, but there are other sources for that. The section on r class effect sizes could have used some more work. (Or perhaps I should know more beforehand?) The final exam may ask questions not explicitly covered in the material; I do not recall any mention of Bonferroni correction, but this is perhaps so basic that it is considered a prerequisite.