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. APPLIED MULTIVARIATE METHODS.
1.1 An Overview of Multivariate Methods
1.2 Two Examples
1.3 Types of Variables
1.4 Data Matrices and Vectors
1.5 The Multivariate Normal Distribution
1.6 Statistical Computing
1.7 Multivariate Outliers
1.8 Multivariate Summary Statistics
1.9 Standardized Data and]or Z Scores
2. SAMPLE CORRELATIONS
2.1 Statistical Tests and Confidence Intervals
2.2 Summary
3. MULTIVARIATE DATA PLOTS
3.1 Three-Dimensional Data Plots
3.2 Plots of Higher Dimensional Data
3.3 Plotting to Check for Multivariate Normality
4. EIGENVALUES AND EIGENVECTORS
4.1 Trace and Determinant
4.2 Eigenvalues
4.3 Eigenvalctors
4.4 Geometrinc descriptions(p=2)
4.5 Geometric descriptions(p=3)
4.6 Geometric descriptions(p>3)
5.PRINCIPAL COMPONENTS ANALYSIS
6.FACTOR ANALYSIS
7.DISCRIMINANT ANALYSIS
8.LOGISTIC REGRESSION METHODS
9.CLUSTER ANALYSIS
10.MEAN VECTORS AND VARIANCE-COVARIANCE MATRICES
11.MULTIVARIATE ANALYSIS OF VARIANCE
12.PREDICTION MODELS AND MULTIVARIATE REGRESSION
APPENDIX A:MATRIX RESULTS
APPENDIX B:WORK ATTITUDES SURVEY
APPENDIX C:FAMILY CONTROL STUDY
REFERENCES
INDEX