Multivariate analysis is commonly used when we have more than one outcome variables for each observation. For instance, a survey of American adults’ physical and mental health might measure each ...

The goal of this talk is to familiarize those in attendance with some common multivariate methods, such as principal component analysis, factor analysis, Hotelling’s T 2, etc. We’ll try to motivate ...

The heterogeneity of oil and gas reservoirs across large resource plays, such as the Bakken, requires operators look at a combination of completion inputs to maximize rates and recoveries. The ...

We consider the problem of testing the hypothesis that the means of a sequence of independent, multivariate normal random variables $x_{1},\ldots ,x_{N}$ are equal ...

Vol. 28, No. 1, Special Multivariate Issue (Mar., 1972), pp. 3-22 (20 pages) Biometrics is a scientific journal emphasizing the role of statistics and mathematics in the biological sciences. Its ...

Demand is at an all-time high for data analysts who can help organizations, technology companies, governments, and nonprofit agencies grasp their organizational, societal, and scientific needs. 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-making. In both traditional ...