Milestone articles have highlighted the frequency and types of statistical errors in research,1–5 yet fundamental errors persist across various disciplines. With a background in biostatistics and over ...

This paper presents a valuable software package, named "Virtual Brain Inference" (VBI), that enables faster and more efficient inference of parameters in dynamical system models of whole-brain ...

Multivariate statistical inference encompasses methods that evaluate multiple outcomes or parameters jointly, allowing researchers to understand complex interdependencies within data. Permutation ...

Statistical learning (SL) is a fundamental cognitive ability enabling individuals to detect and exploit regularities in environmental input. It plays a crucial role in language acquisition, perceptual ...

In the wake of the replication crisis, statistical power has become one of the central issues in debates about the quality of research. The widespread use of tests with low power is seen as a key ...

The Bayesian approach to statistical inference and other data analysis tasks gets its name from Bayes’s theorem (BT). BT specifies that a posterior probability for a hypothesis concerning a data ...

Abstract: The problem of statistical inference in its various forms has been the subject of decades-long extensive research. Most of the effort has been focused on characterizing the behavior as a ...

The Alan Turing Institute, 96 Euston Road, London NW1 2DB, UK This Personal View is intended for early-career researchers who are not yet experts in statistics. The Personal View focuses on common but ...