Applied Multivariate Techniques

Finally! Your Students Don’t Have to be Mathematicians toLearn Multivariate Techniques! Multivariate techniques arefundamental to research analysis but their mathematicalderivations are often overwhelming to students. This exciting newbook takes a gentle approach that introduces students to thevarious multivariate techniques used in business withoutintimidation: The author uses geometry to illustrate concepts so studentsunderstand the various techniques and their application. Matrixalgebra and proofs can also be used by referring to the appendicesof the chapters. Each technique is discussed analytically using a small data setand hand calculations. This gives students a clearer understandingof the technique. Computer outputs from SAS and SPSS are annotated and discussed.Students learn how to interpret the results from these two popularstatistical packages. The chapter–ending pedagogy includes exercises with data setsthat reinforce concepts. Instructor’s Manual: 0–471–13061–3 Also available with thistext is a carefully developed teaching tool for instructors. Itoffers detailed answers to all end of chapter exercises, includingcomputer output for questions which require students to performdata analysis. An additional set of examination questions withanswers are also provided in the manual.

Geometric Concepts of Data Manipulation.

Fundamentals of Data Manipulation.

Principal Components Analysis.

Factor Analysis.

Confirmatory Factor Analysis.

Cluster Analysis.

Two–Group Discriminant Analysis.

Multiple–Group Discriminant Analysis.

Logistic Regression.

Multivariate Analysis of Variance.

Assumptions.

Canonical Correlation.

Covariance Structure Models.

Statistical Tables.

References.

Tables, Figures, and Exhibits.

Index.