Customer perceptions of your company's brand are complex and difficult to predict because of the variety of factors involved. Multivariate analysis uses statistical tools such as multiple regression ...

In semiconductor manufacturing, especially in electrical test data, but also in other parameters, there are often sets of parameters that are very highly correlated. Even a change in the correlation ...

Multivariate analysis in statistics is a set of useful methods for analyzing data when there are more than one variable under consideration. Multivariate analysis techniques may be used for several ...

1. Aspects of multivariate analysis -- 2. Matrix algebra and random vectors -- 3. Sample geometry and random sampling -- 4. The multivariate normal distribution -- 5. Inferences about a mean vector -- ...

We introduce two novel methods for multivariate genome-wide-association meta-analysis (GWAMA) of related traits that correct for sample overlap. A broad range of simulation scenarios supports the ...

The aim of this study was to determine the antioxidant activity, total phenolics, total flavonoid, proanthocyanidins, and anthocyanins content of eight berry species, namely serviceberry, gooseberry, ...

Before we learn how to perform multivariate regression in Excel, it is important to have a refresher on regression as a whole and multivariate regression in particular. One of the hallmarks of human ...

A previous study demonstrated that power against the (unobserved) true effect for the primary end point (PEP) of most phase III oncology trials is low, suggesting an increased risk of false-negative ...

Impact of alcohol dependence on the efficacy of immune checkpoint inhibitors: A comprehensive real-world retrospective cohort analysis. This is an ASCO Meeting Abstract from the 2025 ASCO Annual ...