Background: Scholars and policymakers have criticized public education in developed
countries for perpetuating health and income disparities. Several studies have examined the …

The machine learning community adopted the use of null hypothesis significance testing
(NHST) in order to ensure the statistical validity of results. Many scientific fields however …

Several papers argue that financial economics faces a replication crisis because the
majority of studies cannot be replicated or are the result of multiple testing of too many …

Human activities are fundamentally altering biodiversity. Projections of declines at the global
scale are contrasted by highly variable trends at local scales, suggesting that biodiversity …

In registered reports (RRs), initial peer review and in-principle acceptance occur before
knowing the research outcomes. This combats publication bias and distinguishes planned …

Throughout the last two decades, Bayesian statistical methods have proliferated throughout
ecology and evolution. Numerous previous references established both philosophical and …

Empirical research inevitably includes constructing a data set by processing raw data into a
form ready for statistical analysis. Data processing often involves choices among several …

We introduce a new Empirical Bayes approach for large-scale hypothesis testing, including
estimating false discovery rates (FDRs), and effect sizes. This approach has two key …

In many scientific disciplines, common research practices have led to unreliable and
exaggerated evidence about scientific phenomena. Here we describe some of these …

This article explains the foundational concepts of Bayesian data analysis using virtually no
mathematical notation. Bayesian ideas already match your intuitions from everyday …