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 ...

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 ...

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 ...

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 ...

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 ...

Solve Real-World Problems With Applied Statistics. Applied Statistics is the implementation of statistical methods, techniques, and theories to real-world problems and situations in several fields, ...

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 ...

National precipitation forecasting has for decades been hamstrung by static and inadequate climate models, but new tools are ...

Develop interdisciplinary skills in data science and gain knowledge of statistical analysis, data mining, and machine learning from one of the nation’s top-ranked Tier 1 research institutions. Earn ...