Excellent explanations. Strong examples. Helpful exercises. Highly recommended for anyone who ever has to conduct inferential statistics or read anything that reports a p value or bayes factor.
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.
创建者 Benjamin F
•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 Pavol K
•Amazing course. Definitely worth to accomplish. Highly recommended for every researcher, lecturer, PhD. student or student that is interested in prestent state of art regarding choosen important topics statistics and methodology, especially in Psychology.
创建者 Anna S K
•Great course with practical examples and exercises! Clearly explains typical statistical misunderstandings and provides tips for a responsible and honest scientific practice. I really enjoyed it and already recommended it to all of my colleagues.
创建者 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!
创建者 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.
创建者 Nic B
•This is an excellent course for firming up statistical knowledge and replicable research practices. Likely useful for all psych/cognitive science PhD students and researchers further along who come from the frequentist training tradition.
创建者 Laurent W
•Very good course, with a lot of practical work, which is nice. Also very clear lectures explaining the topics and not too difficult but definitely not too easy exams! Overall fantastic course, which provided me interesting new insights.
创建者 Tim B
•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 Martine K
•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 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!
创建者 Stephen S
•Such a great course. Daniel Lakens does a fantastic job explaining the nuances of statistical repeatability with well thought out examples and helpful tools. This is hands down of the best Coursera courses I've completed.
创建者 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!
创建者 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!)
创建者 Jaroslav G
•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 Srinivas K R
•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 Jonas S
•Very well designed course, from a didactic as well as from an entertainment point of view. I was able to close many gaps in my inferential statistics knowledge and now feel much more confident in my interpretations.
创建者 Rebecca W
•An accessible and interesting course. I learned so much (and refreshed myself on things I should already know!). Thank you so much Dr Lakens for putting together this course. I've been recommending it to everyone!
创建者 Carlos L F
•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 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
创建者 Paul
•Excellent explanations. Strong examples. Helpful exercises. Highly recommended for anyone who ever has to conduct inferential statistics or read anything that reports a p value or bayes factor.
创建者 Alvaro M B
•Easy to follow, well structured, good references, empathy of presenter. I will recomend this to other friends who made Black Belt certification and still don't have clear what the Pvalue is for.
创建者 Yaron K
•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.
创建者 Andrés 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.
创建者 Miroslav R
•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 Bob H
•This is a top-notch course. The ground (especially pitfalls) is very well covered, and useful free tools are engaged (R, G*Power, prof's own spreadsheets for calculating effect size).