This important study reports three experiments examining how the subjective experience of task regularities influences perceptual decision-making. Although the evidence linking subjective ratings to ...

We’re proud to launch Ellie Solo, a new individual version of Ellie built specifically for individual data professionals, freelancers, and small teams. HELSINKI, UUSIMAA, FINLAND, January 5, 2026 ...

First, institutions must ensure that synthetic datasets are continuously recalibrated against fresh, real-world evidence. The ...

This book, “Statistical Modeling and Computation,” provides a unique introduction to modern statistics from both classical and Bayesian perspectives. It also offers an integrated treatment of ...

The first step in conducting a regression-based study is to specify a model. In real applications, this is usually the most challenging step - deciding which variables “belong” in the model and which ...

Data modeling refers to the architecture that allows data analysis to use data in decision-making processes. A combined approach is needed to maximize data insights. While the terms data analysis and ...

For years, the artificial intelligence industry has followed a simple, brutal rule: bigger is better. We trained models on massive datasets, increased the number of parameters, and threw immense ...

Abstract: Assumptions play a pivotal role in the selection and efficacy of statistical models, as unmet assumptions can lead to flawed conclusions and impact decision ...

Social media posts about unemployment can predict official jobless claims up to two weeks before government data is released, ...

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 ...