Statistical modeling continues to deliver distinct value to businesses both independent of, and in concert with, machine learning. “Artificial intelligence” (AI) and “machine learning” are among the ...

Livestock agriculture (e.g., dairy, beef, pork, poultry) in the United States is tending rapidly toward operations where a large number of animals are concentrated in a relatively small area. The ...

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 ...

In a recent article published in the eLife Journal, researchers launched a possum excreta surveillance program across 350 km 2 in the Mornington Peninsula near South Melbourne, Australia. The study ...

In this module, we will introduce the basic conceptual framework for statistical modeling in general, and linear statistical models in particular. In this module, we will learn how to fit linear ...

A model is proposed for the study of plant breeding where the self-fertilization rate is of importance. The model can be used to provide convenient maximum likelihood estimation of the ...

Okay. Good afternoon, everybody. Thank you for joining us. I'm Doug Tsao, Senior Analyst at H.C. Wainwright. We are thrilled today for what I think is a very unique event. We are joined by Professor ...

A study has validated a new statistical model that uses multiple standardized test scores over time to predict future academic performance. The dynamic measurement model accurately predicted academic ...

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 ...

A study of migrants in Italy has shown how statistical modeling can help improve the identification of neglected tropical disease (NTD) infections. NTDs are a group of 21 diseases that ...