Analyzing Multivariate Data has 19 ratings and 1 review. Dan said: One of the clearest books I’ve ever read on certain statistical learning techniques: m. Request PDF on ResearchGate | On Jan 1, , James M Lattin and others published Analyzing Multivariate Data. Data Matters as an introductory statistics text for undergraduates in any fi eld of study. Analyzing Multivariate Data, by James M. LATTIN,. J. Douglas.

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By dsta our website you agree to our use of cookies. Home Contact Us Help Free delivery worldwide. Description Offering the latest teaching and practice of applied multivariate statistics, this text is perfect for students who need an applied introduction to the subject. Lattin, Carroll, and Green have created a text multivaraite speaks to the needs of applied students who have advanced beyond the beginning level, but are not advanced statistics majors.


The text provides a three-part structure. First, the authors begin each major topic by developing students’ statistical intuition through applications. Then, anaoyzing providing illustrative examples for support. Finally, for those courses where it will be valuable, they describe relevant mathematical underpinnings with vectors and matrix algebra. Additionally, each chapter follows a standard format.

This format begins by discussing a general set of research objectives, followed by illustrative examples of problems in different areas. Then it provides an explanation of how each method works, followed by a sample problem, application of the technique, and interpretation of results.

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Table of contents Part One: The Nature of Multivariate Data. Overview of Multivariate Methods. Format of Succeeding Chapters. Geometric Interpretation of Operations. Questions Regarding the Application of Principal Components.

Perceptions of Ready-to-Eat Cereals. Questions Regarding the Application of Factor Analysis. How Does it Work? How Does It Work? A Note on Model Validation. Objectives of Cluster Analysis. Measures of Distance, Dissimilarity, and Density. Questions Regarding the Application of Cluster Analysis.


Analyzing Multivariate Data – James M. Lattin, J. Douglas Carroll, Paul E. Green – Google Books

Questions Regarding the Application of Canonical Correlation. Structural Equation Models with Latent Variables. Structural Equations with Latent Variables: Modeling the Adoption of Innovation.

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Analyzing Multivariate Data

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