Innovative statistical method helps determine ideal threshold times in restricted mean survival time analyses. The restricted mean survival time (RMST) analysis technique was introduced in health care ...

A deep learning framework combines convolutional and bidirectional recurrent networks to improve protein function prediction from genomic sequences. By automating feature extraction and capturing long ...

Information on Earth's biodiversity is increasingly collected using DNA-, image- and audio-based sampling. At the same time, new statistical analysis methods are being developed to make more out of ...

Misuse of statistics in medical and sports science research is common and may lead to detrimental consequences to healthcare. Many authors, editors and peer reviewers of medical papers will not have ...

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 ...

Kevin Dayaratna was Director of the Center for Data Analysis and Chief Statistician for Heritage. A variety of statistical tools can detect potential breaches in the integrity of elections. These ...

Researchers have developed a machine learning model that could better measure baseball players' and teams' short- and long-term performance, compared to existing statistical analysis methods for the ...

Let’s start with a definition of Applied Statistics: Applied Statistics is the root of data analysis. The practice of applied statistics involves analyzing data to help define and determine an ...

Statistics influence nearly everything. That is, the information and context derived from statistical analysis help to shape important decisions that have local, national, and global impacts. For ...