Chevron Left
Volver a Improving your statistical inferences

Opiniones y comentarios de aprendices correspondientes a Improving your statistical inferences por parte de Universidad Técnica de Eindhoven

4.9
estrellas
731 calificaciones

Acerca del 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"...

Principales reseñas

MS

13 de may. de 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.

VM

10 de jul. de 2021

Solid course which taught me how to interpret p-values in a variety of contexts and taught me to not just to consider but (systematic and practical) ways of how to correct for publication bias.

Filtrar por:

101 - 125 de 238 revisiones para Improving your statistical inferences

por Gregory D

26 de mar. de 2018

por Glenn

21 de jun. de 2017

por Andres F P A

16 de ago. de 2021

por Jayadev H

11 de may. de 2018

por Oleksandr H

25 de nov. de 2016

por Wilte Z

23 de oct. de 2016

por Iván Z A

15 de feb. de 2017

por Ernesto M

30 de jul. de 2018

por Muhammad T S

8 de nov. de 2017

por Moos L

6 de nov. de 2016

por Eloy A O

23 de jun. de 2020

por Nicholas

28 de abr. de 2019

por Sanjeev P

13 de nov. de 2016

por Sebastian U

26 de mar. de 2018

por Tyron J

8 de ene. de 2022

por Ted T

29 de mar. de 2020

por Michael E

25 de jun. de 2017

por Ляшенко І В

6 de ago. de 2020

por Kathryn S

9 de dic. de 2017

por Jingbo H

12 de jun. de 2018

por Mathew L

4 de jun. de 2017

por Jana H

4 de mar. de 2017

por Romain R

10 de ene. de 2019

por Munzar A S

10 de abr. de 2020

por Petr Č

14 de abr. de 2022