Applied Multivariate Statistical Analysis (Classic Version), 6th edition
Your access includes:
 Search, highlight, and take notes
 Easily create flashcards
 Use the app for access anywhere
 14day refund guarantee
$10.99per month
4month term, pay monthly or pay $43.96
Learn more, spend less

Special partners and offers
Enjoy perks from special partners and offers for students

Find it fast
Quickly navigate your eTextbook with search

Stay organized
Access all your eTextbooks in one place

Easily continue access
Keep learning with autorenew
Overview
Hallmark features of this title
 Accessible level: Presents the concepts and methods of multivariate analysis in a way that is readily understandable by readers who have taken 2 or more statistics courses.
 Organization and approach: Contains the methodological tools of multivariate analysis in Chapters 5  12, with a discussion that is direct and uncluttered. Ample student assistance in navigating difficult topics is provided.
 An abundance of examples and exercises based on real data: Includes in some cases snapshots of the corresponding SAS output.
 Targeted presentation of key concepts.
 Emphasis on applications of multivariate methods.
 A clear and insightful explanation of multivariate techniques.
Published by Pearson (May 16th 2023)  Copyright © 2023
ISBN13: 9780137980963
Subject: Advanced Statistics
Category: Multivariate Statistics
Table of contents
(Note: Each chapter begins with an Introduction and concludes with Exercises and References.
I. GETTING STARTED
 1. Aspects of Multivariate Analysis
 Applications of Multivariate Techniques. The Organization of Data. Data Displays and Pictorial Representations. Distance. Final Comments.
 2. Matrix Algebra and Random Vectors
 Some Basics of Matrix and Vector Algebra. Positive Definite Matrices. A SquareRoot Matrix. Random Vectors and Matrices. Mean Vectors and Covariance Matrices. Matrix Inequalities and Maximization. Supplement 2A Vectors and Matrices: Basic Concepts.
 3. Sample Geometry and Random Sampling
 The Geometry of the Sample. Random Samples and the Expected Values of the Sample Mean and Covariance Matrix. Generalized Variance. Sample Mean, Covariance, and Correlation as Matrix Operations. Sample Values of Linear Combinations of Variables.
 4. The Multivariate Normal Distribution
 The Multivariate Normal Density and Its Properties. Sampling from a Multivariate Normal Distribution and Maximum Likelihood Estimation. The Sampling Distribution of `X and S. LargeSample Behavior of `X and S. Assessing the Assumption of Normality. Detecting Outliners and Data Cleaning. Transformations to Near Normality.
II. INFERENCES ABOUT MULTIVARIATE MEANS AND LINEAR MODELS
 5. Inferences About a Mean Vector
 The Plausibility of …m0 as a Value for a Normal Population Mean. Hotelling's T^{2} and Likelihood Ratio Tests. Confidence Regions and Simultaneous Comparisons of Component Means. Large Sample Inferences about a Population Mean Vector. Multivariate Quality Control Charts. Inferences about Mean Vectors When Some Observations Are Missing. Difficulties Due To Time Dependence in Multivariate Observations. Supplement 5A Simultaneous Confidence Intervals and Ellipses as Shadows of the pDimensional Ellipsoids.
 6. Comparisons of Several Multivariate Means
 Paired Comparisons and a Repeated Measures Design. Comparing Mean Vectors from Two Populations. Comparison of Several Multivariate Population Means (OneWay MANOVA). Simultaneous Confidence Intervals for Treatment Effects. TwoWay Multivariate Analysis of Variance. Profile Analysis. Repealed Measures, Designs, and Growth Curves. Perspectives and a Strategy for Analyzing Multivariate Models.
 7. Multivariate Linear Regression Models
 The Classical Linear Regression Model. Least Squares Estimation. Inferences About the Regression Model. Inferences from the Estimated Regression Function. Model Checking and Other Aspects of Regression. Multivariate Multiple Regression. The Concept of Linear Regression. Comparing the Two Formulations of the Regression Model. Multiple Regression Models with Time Dependant Errors. Supplement 7A The Distribution of the Likelihood Ratio for the Multivariate Regression Model.
III. ANALYSIS OF A COVARIANCE STRUCTURE
 8. Principal Components
 Population Principal Components. Summarizing Sample Variation by Principal Components. Graphing the Principal Components. LargeSample Inferences. Monitoring Quality with Principal Components. Supplement 8A The Geometry of the Sample Principal Component Approximation.
 9. Factor Analysis and Inference for Structured Covariance Matrices
 The Orthogonal Factor Model. Methods of Estimation. Factor Rotation. Factor Scores. Perspectives and a Strategy for Factor Analysis. Structural Equation Models. Supplement 9A Some Computational Details for Maximum Likelihood Estimation.
 10. Canonical Correlation Analysis
 Canonical Variates and Canonical Correlations. Interpreting the Population Canonical Variables. The Sample Canonical Variates and Sample Canonical Correlations. Additional Sample Descriptive Measures. Large Sample Inferences.
IV. CLASSIFICATION AND GROUPING TECHNIQUES
 11. Discrimination and Classification
 Separation and Classification for Two Populations. Classifications with Two Multivariate Normal Populations. Evaluating Classification Functions. Fisher's Discriminant Function…ñSeparation of Populations. Classification with Several Populations. Fisher's Method for Discriminating among Several Populations. Final Comments.
 12. Clustering, Distance Methods and Ordination
 Similarity Measures. Hierarchical Clustering Methods. Nonhierarchical Clustering Methods. Multidimensional Scaling. Correspondence Analysis. Biplots for Viewing Sample Units and Variables. Procustes Analysis: A Method for Comparing Configurations.
Appendix
 Standard Normal Probabilities. Student's tDistribution Percentage Points. …c2 Distribution Percentage Points. FDistribution Percentage Points. FDistribution Percentage Points (…a = .10). FDistribution Percentage Points (…a = .05). FDistribution Percentage Points (…a = .01).
Data Index
Subject Index
Your questions answered
Pearson+ is your onestop shop, with eTextbooks and study videos designed to help students get better grades in college.
A Pearson eTextbook is an easy‑to‑use digital version of the book. You'll get upgraded study tools, including enhanced search, highlights and notes, flashcards and audio. Plus learn on the go with the Pearson+ app.
Your eTextbook subscription gives you access for 4 months. You can make a one‑time payment for the initial 4‑month term or pay monthly. If you opt for monthly payments, we will charge your payment method each month until your 4‑month term ends. You can turn on auto‑renew in My account at any time to continue your subscription before your 4‑month term ends.
When you purchase an eTextbook subscription, it will last 4 months. You can renew your subscription by selecting Extend subscription on the Manage subscription page in My account before your initial term ends.
If you extend your subscription, we'll automatically charge you every month. If you made a one‑time payment for your initial 4‑month term, you'll now pay monthly. To make sure your learning is uninterrupted, please check your card details.
To avoid the next payment charge, select Cancel subscription on the Manage subscription page in My account before the renewal date. You can subscribe again in the future by purchasing another eTextbook subscription.
Channels is a video platform with thousands of explanations, solutions and practice problems to help you do homework and prep for exams. Videos are personalized to your course, and tutors walk you through solutions. Plus, interactive AI‑powered summaries and a social community help you better understand lessons from class.
Channels is an additional tool to help you with your studies. This means you can use Channels even if your course uses a non‑Pearson textbook.
When you choose a Channels subscription, you're signing up for a 1‑month, 3‑month or 12‑month term and you make an upfront payment for your subscription. By default, these subscriptions auto‑renew at the frequency you select during checkout.
When you purchase a Channels subscription it will last 1 month, 3 months or 12 months, depending on the plan you chose. Your subscription will automatically renew at the end of your term unless you cancel it.
We use your credit card to renew your subscription automatically. To make sure your learning is uninterrupted, please check your card details.