Machine learning and artificial intelligence wouldn't be possible without the statistical models that underpin their analytic capabilities. A Cornell statistician and his colleague have developed a ...

An alternative statistical method honed and advanced by Cornell researchers can make clinical trials more reliable and trustworthy while also helping to remedy what has been called a "replicability ...

The Statistical & Data Sciences (SDS) Program links faculty and students from across the college interested in learning things from data. At Smith, students learn statistics by doing—class time ...

Method comparison studies aim to evaluate whether two or more measurement techniques yield sufficiently similar results to be used interchangeably. Traditional approaches such as linear regression and ...

“Sweet are the uses of adversity, which, like the toad, ugly and venomous, wears yet a precious jewel in his head.” – William Shakespeare, “As You Like It” (II.1.12–17) Despite extensive resilience ...

Precision oncology exploits genomic, immunologic, and other biomarkers to drive discovery, drug development, and clinical care for patients with cancer. Precision oncology helps devise individualized ...

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-making. In both traditional ...

A statistical approach being used to support a new class of Alzheimer's drugs may lead to overstated claims about how the drugs work, according to a new study led by researchers at the Brown ...

Across modern data-intensive disciplines, the union of numerical computation, statistics, and machine learning has become ...

A relatively simple statistical analysis method can more accurately predict the risk of landslides caused by heavy rain, according to a study coordinated by Brazilian researchers affiliated with the ...

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