Fuzzy statistics and random variables represent a progressive fusion of traditional probability theory with the principles of fuzzy logic, enabling the treatment of imprecision and vagueness ...

Non-discretionary or environmental variables are regarded as important in the evaluation of efficiency in Data Envelopment Analysis (DEA), but there is no consensus on the correct treatment of these ...

Multidimensional data arise when a number of different response variables are required to measure the outcome of interest. Examples of such outcomes include quality of life, cognitive ability, and ...

UCSF's interactive data platform allows users to drill down into 150 social determinants of health variables. This data, layered with EHR data, can give researchers and clinicians invaluable ...

The simplest form of regression in Python is, well, simple linear regression. With simple linear regression, you're trying to ...

The AI Leadership Brain Trust Series identifies 50 key skills to advance AI skill competencies. This blog discusses the importance of statistical literacy to ensure Board Directors and C-levels ...

Programming C without variables is like, well, programming C without variables. They are so essential to the language that it doesn’t even require an analogy here. We can declare and use them… ...

The Statistics and Data Science curriculum links faculty and students from across the college interested in learning things from data. One important goal is to prepare students for careers in data ...