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

4.9
estrelas
625 classificações
203 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

PP
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.

YK
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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101 — 125 de 201 Avaliações para o Improving your statistical inferences

por 侯静波

12 de Jun de 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.

por Mathew L

4 de Jun de 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.

por Jana H

4 de Mar de 2017

Wonderful course! It was really well-conceived and I learned a lot. Would definitely recommend it to everyone interested in statistics!

por Romain R

10 de Jan de 2019

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 !

por Munzar A S

10 de Abr de 2020

Fabulous course! Points out a lot of the nonsense going on in psychological research, how we can spot it, and how we can do better!

por marcus n

4 de Fev de 2017

Great high level overview of intermediate applied statistics. The instructors presentation skills and pace are very good as well.

por Maxim P

22 de Mar de 2020

Such a wonderful course, I really enjoyed the walkthrough. Also, I'd like to note the perfect English language of the lecturer.

por Dennis H

4 de Dez de 2018

excellent refresher and expansion on frequentists stats (interpretation) and nice intro to bayesian stats. highly recommended.

por Katia D

11 de Fev de 2018

Great course! Although I was struggling with lecture 2 (Bayesian Statistics)––It was very mathsy and a bit difficult to follow.

por Cesar Y

25 de Fev de 2019

Practico sin hacer a un lado lo teorico, te dan un marco mucho mas amplio para la interpretacion y planteamiento de hipotesis

por Agustin E C F

5 de Nov de 2019

This is a great course!. It tackles common misbeliefs and approaches the topics both in a technical and coloquial manner.

por Ezra H

19 de Mai de 2020

Very well structured. Every week covered a different important topic. Overall a useful course for empirical researchers.

por Maojie T

1 de Jan de 2020

I think it's a useful course for me, but I think some content in the last week is a little bit trivial for me...

por John B

17 de Jul de 2018

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

por Davide F S

21 de Mai de 2017

Clear, concise, and engaging explanation of many statistical concepts that can be readily applied in research.

por Amy M

2 de Nov de 2016

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

por Lydia A G

28 de Mai de 2020

Highly recommendable course. It puts clarity from the most basic concepts to some other new insights.

por Sandra V

10 de Dez de 2016

Extremely useful cours, especially the first 5 weeks! Pleasant and enjoyable. Definitely recommended!

por Fengyuan L

31 de Jul de 2020

excellent course. It solves lots of my question over the p value as well as the statistic analysis.

por Habiba A

29 de Dez de 2016

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

por Thijs

14 de Ago de 2019

Great course. Already had some knowledge about statistics, but this course really improved it.

por Mr. J

24 de Fev de 2020

Superbly Done synopsis of statistical gotchas and best practice against them. Very Valauble.

por Morio C

2 de Jan de 2020

Great course, clear and helpful. I will definitely recommend it to colleagues and students.

por Jose M S

17 de Jun de 2017

Quite interesting and well structured. The contents of this course deserve a wide audience.

por Patrick H

10 de Ago de 2020

This course should be taken by any psychologist (and actually anyone who does statistics)