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 ...

Count data modelling occupies a central role in statistical applications across diverse disciplines including epidemiology, econometrics and engineering. Traditionally, the Poisson distribution has ...

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 ...

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 ...

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 ...

Researchers have created a statistical method that may allow public health and infectious disease forecasters to better predict disease reemergence, especially for preventable childhood infections ...

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 ...