This study presents valuable findings from a spatiotemporal analysis of arbovirus case notification data from 2013 to 2020 in Brazil, reporting associations between covariates representing potential ...

Some of the models used to forecast everything from financial trends to animal populations in an ecosystem are incorrect, ...

Unanet's Kim Koster explains how Probability of Award helps GovCons move from intuition to data-driven forecasting and ...

The authors used a Bayesian modeling framework to fit behavior and serotonin neuron activity to reward history across multiple timescales. A key goal was to distinguish value coding from other ...

Statistical models predict stock trends using historical data and mathematical equations. Common statistical models include regression, time series, and risk assessment tools. Effective use depends on ...

When we reject the null hypothesis, we are essentially saying that the observed data provides sufficient evidence to conclude ...