For more than half a century, data analysts have used graphs to represent statistical models. In particular, graphical "conditional independence" models have emerged as a useful class of models.

A second course in statistics with an emphasis on data analysis with applications in the social sciences. Students will gain hands on experience using R-- a programming language and software ...

Data that have a multilevel structure occur frequently across a range of disciplines, including epidemiology, health services research, public health, education and sociology. We describe three ...

Statistical modeling lies at the heart of data science. Well-crafted statistical models allow data scientists to draw conclusions about the world from the limited information present in their data. In ...

A second course in statistics with an emphasis on data analysis with applications in the social sciences. Students will gain hands on experience using R-- a programming language and software ...

In the process of business development planning for units, the demand for precise and comprehensive data support is becoming increasingly urgent. Beijing's Runquan Intelligent Data Collaborative ...

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 ...

Enhance your skills in energy statistical analysis with our expanded three-day workshop. Dive deep into crucial topics like risk quantification and pricing models using practical exercises in Excel.