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 …
Instructor Details
Courses : 2
Specification: Improving your statistical inferences

54 reviews for Improving your statistical inferences
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Helen L –
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.
Aishwar D –
Thank you Daniel Lakens for creating and sharing this course in the way you have done. The content is very appropriate for any one anyone who is looking to work with Inferential Statistics. Many thanks
Danielle L –
An excellent, informative, organized course. Highly recommended!
Yoel S –
One of the best online courses I’ve ever taken! (completed it just now). Great lectures, great materials, great assignments. Links and information for anyone wanting to go deeper on any topic. Brilliant and engaing lecturer who provides the information with so much passion and interest that it “catches on” to you. I especially liked how actual studies are used as examples for learning/assignments. Bottom line – in my opinion it’s a must do course to anyone who is interested in inferential statistics.
Dashakol –
I dropped the course at Lecture 1.2 when it was supposed to really teach me what is p–value but it failed. A 20 min video without telling much about p–value and also adding more confusion and unanswered questions at the end. Like what is p–value distribution? I expected to receive a decent step by step tutorial on statistics starting from basics but it was just another convoluted stuff on statistics.
Jose J P N –
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.
Lior Z –
Great course! Highly recommended. One thing to improve – I would like to see more theory behind the different effect sizes (eta–squared/omega squared/etc)
Jan N –
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.
Marija A –
I find this course very useful, since these are topics that do not stick when you are completely new to statics, but are very useful once you have few years experience in practice. My only remark is that sometimes the multiple choice answers in the quizzes were not clear enough, so a bit confusing.
Alicia S J –
Good pacing and ratio of exercises/lecture. I found the assignments very useful and the instructions easy to follow. Comparing my performance on the pre–tests and pop quizzes at the beginning of the course to those at the end clearly demonstrates that the coursework honed my stats intuition, and I’m very grateful! The only critical feedback I have is that occasionally, I found the wording of test/quiz questions to be a bit confusing. Thanks!
Bertin –
This course is amazing, dynamic and entertaining. Daniel Lakens is brilliant.
Nareg K –
Great course!
Dennis H –
excellent refresher and expansion on frequentists stats (interpretation) and nice intro to bayesian stats. highly recommended.
Jason L –
I really enjoyed the course and found it challenging at times. Its definitely worth the time and effort as my knowledge has improved dramatically. I have gained knowledge which will be really helpful in the future for correctly interpreting current literature as well as future reporting of data and building research ideas. I also appreciate all the effort put into this course and the tools provided which will be beneficial to me in the future. I have saved a lot of the webpages and tools for future reference and will definitely use them when beginning research as well as examining current literature. Excellent
Leanne C –
Very informative course, well taught and with lots of useful practice built into the assignments.
Romain R –
Great overview of statistics and philosophy of science. Now I know what to tell my students when they ask me about p–values. At last !
Daniel K –
Thanks to the creators of this course for putting together an engaging curriculum. One note of criticism is that the assignments for Week 5 required G*power software which as far as I can tell is not available on Linux (I’m running Ubuntu). The practical examples, specifically the example of the impact of Facebook’s A/B testing were particularly interesting. I think this course has improved the tools I have at my disposal for interpreting the language commonly used in academic reporting, and I’m confident the information and tools presented will help in my own research in the coming years.
Richard M –
Great course. A lot of topics introduced and explored. Well worth the time.
Esthelle E –
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!
Bruno V –
Thank you daniel, very educational, I learned a lot
Cesar A Y B –
Practico sin hacer a un lado lo teorico, te dan un marco mucho mas amplio para la interpretacion y planteamiento de hipotesis
Peter K –
Excellent course. I learned a lot about inference.
Maureen M –
The best MOOC in statistis ever!
Andres C M –
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.
Reuben A –
The best statistics course I have ever taken
Nicholas –
Fantastic course on inference, difference between frequentist and Bayesian concepts like p–values, confidence and credible intervals, and validity.
Rodney K –
Very comprehensive and enjoyable course, highly recommended.
Kevin H –
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.
Daniel A L –
As an early career scientist, this course helped me get a solid foundation on statistical inferences. After years of accumulating vaguely–organised statistical concepts and procedures, now I am confident I have mastered the basics. Definitely the best course I’ve had in a long time!
Pepe V C –
The explanations from Daniel are awesome… I am understanding p values in a manner I never did before.
Yonathan M P –
Amazing course! Tons of insights and original thinking!
Emmanuel k A –
I started just today and I’m beginning to love the course
Andreas K –
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.
Julien B –
Amazing course! Many thanks to Daniel Lakens for the time spent on this. It’s really useful and I’ve learned so many things I will use to make better research.
ese10 –
Very informative.
Shambhavi –
Excellent course, taught well with very useful assignments. Would recommend!
Thijs –
Great course. Already had some knowledge about statistics, but this course really improved it.
Ryan M –
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!
Robert H –
Excellent—an absolute must for all PhD students and early–career researchers
Shunan H –
I like this course so much, Prof. Jeff makes all lectures clearly, but some answers and details in quizs are not mentioned in video and I have some problems with them.
Meghana J –
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!)
Agustin E C F –
This is a great course!. It tackles common misbeliefs and approaches the topics both in a technical and coloquial manner.
Tomas d l R M –
Amazing course! Very useful to researchers in any area
Max K –
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!
Max R –
It was nice. I initially hoped the course would have made some technical details intuitively graspable, but it was fine as it is.
Pablo M B –
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!
Jose M O –
An excellent course: full of training and insightful approaches. It peruses and smartly debunks the most ingrained rituals associated with statistical reasoning and practice (especially for a researcher psychologist), sometimes with a grain of subtle humor. Plenty of support literature and invaluable online tools (and others such as excel files) to understand and deal with each subject in both the assignments and hopefully, in future work. Very pleased to have taken the course!
Sergey L –
The course is full of useful insights and practices. I can definitely recommend it!
Morio C –
Great course, clear and helpful. I will definitely recommend it to colleagues and students.
Sarah W –
Thanks Lakens
Maxim P –
Such a wonderful course, I really enjoyed the walkthrough. Also, I’d like to note the perfect English language of the lecturer.
Rossella M –
Really useful and interesting course!
Mrinalini R –
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!
Ted T –
Top quality course. Learnt a lot thanks to the very helpful and clear teaching. Put the equivalent course at my actual university to shame.