Chevron Left
Retour à Improving your statistical inferences

Avis et commentaires pour d'étudiants pour Improving your statistical inferences par Université technique d'Eindhoven

4.9
étoiles
731 évaluations

À propos du cours

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"...

Meilleurs avis

MS

13 mai 2021

Eye opening course. My first introduction to some of the issues surrounding p-values as well as how to better utilize them and what they truly represent. My first introduction to effect sizes as well.

PP

28 juin 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.

Filtrer par :

1 - 25 sur 238 Avis pour Improving your statistical inferences

par Shan X

25 juin 2018

par Daniel A L

25 mai 2019

par Bartek

30 oct. 2016

par Luis A

21 août 2017

par Stefan W

28 déc. 2016

par Alex G

26 oct. 2016

par Julien B

21 juil. 2019

par Pepe V C

1 juin 2019

par Yonathan M P

8 juin 2019

par Aicha M A N

12 nov. 2020

par Farhan N

21 mai 2018

par Benedikt L

22 juin 2018

par Andreas K

15 juil. 2019

par Constantin Y P

17 mai 2017

par Wessel G

16 août 2022

par Nicholas J

23 janv. 2018

par Maxine S

3 janv. 2022

par Oviya M

18 juil. 2020

par Răzvan J

30 mai 2017

par Jason L

7 déc. 2018

par Helén L

17 août 2018

par Tyson W B

23 févr. 2018

par zuzana n

18 sept. 2020

par Oaní d S d C

16 août 2018

par Yoel S

15 sept. 2018