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Comentários e feedback de alunos de Improving your statistical inferences da instituição Universidade Tecnológica de Eindhoven

627 classificações
205 avaliações

Sobre o curso

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"...

Melhores avaliações

28 de Jun de 2020

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.

1 de Mar de 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.

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51 — 75 de 203 Avaliações para o Improving your statistical inferences

por Benjamin F

16 de Ago de 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 :)

por Pavol K

16 de Ago de 2017

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.

por Anna S K

22 de Mar de 2018

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.

por Ryan M

7 de Set de 2019

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!

por Jose J P N

9 de Out de 2018

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.

por Nic B

17 de Jul de 2017

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.

por Laurent W

6 de Out de 2020

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.

por Tim B

5 de Jan de 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.

por Martine K

21 de Jun de 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.

por Esthelle E

23 de Jan de 2019

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!

por Stephen S

10 de Jun de 2020

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.

por Max K

28 de Nov de 2019

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!

por Meghana J

17 de Out de 2019

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!)

por Jaroslav G

5 de Fev de 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.

por Srinivas K R

9 de Out de 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.

por Jonas S

16 de Nov de 2016

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.

por Rebecca W

17 de Jul de 2017

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!

por Carlos L F

18 de Jul de 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.

por Aishwar D

25 de Ago de 2018

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

por Paul

29 de Jun de 2020

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.

por Alvaro M B

23 de Fev de 2020

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.

por Yaron K

2 de Mar de 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.

por Andrés C M

25 de Mar de 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.

por Miroslav R

22 de Fev de 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

por Bob H

6 de Out de 2017

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).