Discover the importance of homoskedasticity in regression models, where error variance is constant, and explore examples that illustrate this key concept.

Tao: Today there are a lot of very tedious types of mathematics that we don’t like doing, so we look for clever ways to get ...

Probability underpins AI, cryptography and statistics. However, as the philosopher Bertrand Russell said, “Probability is the ...

Large language models struggle to solve research-level math questions. It takes a human to assess just how poorly they perform.

GRAND FORKS — The North Dakota Department of Public Instruction has partnered with national education nonprofit New Classrooms Innovation Partners to design a new, statewide math model. In December ...

Opinion polarization is often considered as the primary driver of social friction, leading to exhaustive efforts to force a consensus. However, new research suggests a more pragmatic goal: reducing ...

A few days ago, Google finally explained why its best AI image generation model is called Nano Banana, confirming speculation that the moniker was just a placeholder that stuck after the model went ...

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 ...

Abstract: This paper describes software for designing homodesmic reactions using the example of a cyclic compound of cyclobutanecarbonitrile. The homodesmic method showed high reliability of the ...

New research demonstrates how mathematical modeling can predict outbreaks of toxic fungi in Texas corn crops -- offering a potential lifeline to farmers facing billions in harvest losses. New research ...

A few months before the 2025 International Mathematical Olympiad (IMO) in July, a three-person team at OpenAI made a long bet that they could use the competition’s brutally tough problems to train an ...