Real-world problems and data sets are the backbone of this groundbreaking book. Applied Multivariate Statistics with SAS Software, Second Edition provides a unique approach to the topic, integrating ...

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

Discover how multivariate models use multiple variables for investment forecasting, risk analysis, and decision-making in ...

Larry Hatcher, Ph.D. and Edward J. Stepanski, Ph.D. Introduction: The Basics of One-Way ANOVA, Between-Groups Design Example with Significant Differences between Experimental Conditions Understanding ...

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 ...

Proceeding from the idea of Chernoff (1971, 1973) of representing multivariate data by faces, a new face is proposed in which the face parameters of the left and the right side can be varied ...

Multivariate data analysis (MVDA) is being used to effectively handle complex datasets generated by process analytical technology (PAT) in biopharmaceutical process development and manufacturing.

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 ...