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Home > Mathematics and Science Textbooks > Mathematics > Probability and statistics > Applied Multivariate Methods for Data Analysts
Applied Multivariate Methods for Data Analysts

Applied Multivariate Methods for Data Analysts

          
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About the Book

Statisticians and nonstatisticians alike will appreciate this modern and comprehensive new text. Dallas Johnson uses real-life examples and explains the when to, why to, and how to of numerous multivariate methods, stressing the importance and practical application of each. He keeps technical details to a minimum for greater student understanding. Students will be able to DO multivariate analyses when they complete this book. Drawing on nearly 20 years of experience teaching public seminars and college courses in applied multivariate methods. Johnson emphasizes those aspects that have been most useful to practitioners trying to solve real problems using real data.

Table of Contents:
1. Applied multivariate methods. An Overview of Multivariate Methods. Two Examples. Types of Variables. Data Matrices and Vectors. The Multivariate Normal Distribution. Statistical Computing. Multivariate Outliers. Multivariate Summary Statistics. Standardized Data and/or z-Scores. Exercises. 2. Sample correlations. Statistical Tests and Confidence Intervals. Summary. Exercises. 3. Multivariate data plots. Three-Dimensional Data Plots. Plots of Higher Dimensional Data. Plotting to Check for Multivariate Normality. Exercises. 4. Eigenvalues and eigenvectors. Trace and Determinant. Eigenvalues. Eigenvectors. Geometrical Descriptions (p=2). Geometrical Descriptions (p=3). Geometrical Descriptions (p>3). Exercises. 5. Principal components analysis. Reasons For Doing a PCA. Objectives of a PCA. PCA on the Variance-Covariance Matrix, Sigma. Estimation of Principal Components. Determining the Number of Principal Components. Caveats. PCA on the Correlation Matrix, P. Testing for Independence of the Original Variables. Structural Relationships. Statistical Computing Packages. Exercises. 6. Factor analysis. Objectives of an FA. Caveats. Some History on Factor Analysis. The Factor Analysis Model. Factor Analysis Equations. Solving the Factor Analysis Equations. Choosing the Appropriate Number of Factors. Computer Solutions of the Factor Analysis Equations. Rotating Factors. Oblique Rotation Methods. Factor Scores. Exercises. 7. Discriminant analysis. Discrimination for Two Multivariate Normal Populations. Cost Functions and Prior Probabilities (Two Populations). A General Discriminant Rule (Two Populations). Discriminant Rules (More Than Two Populations). Variable Selection Procedures. Canonical Discriminant Functions. Nearest Neighbour Discriminant Analysis. Classification Trees. Exercises. 8. Logistic regression methods. The Logit Transformation. Logistic Discriminant Analysis (More than Two Populations.) Exercises. 9. Cluster analysis. Measures of Similarity and/or Dissimilarity. Graphical Aids in Clustering. Clustering Methods. Multidimensional Scaling. Exercises. 10. Mean vectors and variance-covariance matrices. Inference Procedures for Variance-Covariance Matrices. Inference Procedures for a Mean Vector. Two Sample Procedures. Profile Analyses. Additional Two Groups Analyses. Exercises. 11. Multivariate analysis of variance. manova. Dimensionality of the Alternative Hypothesis. Canonical Variates Analysis. Confidence Regions for Canonical Variates. Exercises. 12. Prediction models and multivariate regression. Multiple Regression. Canonical Correlation Analysis. Factor Analysis and Regression. Exercises. Appendices: Matrix results, quadratic forms, eigenvalues and eigenvectors, distances and angles, miscellaneous results; work attitudes survey, data file structure, SPSS data entry commands, SAS data entry commands; family control study.


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Product Details
  • ISBN-13: 9780534237967
  • Publisher: Cengage Learning, Inc
  • Publisher Imprint: Wadsworth Publishing Co Inc
  • Edition: Annotated edition
  • Language: English
  • Weight: 1134 gr
  • ISBN-10: 0534237967
  • Publisher Date: 06 Feb 1998
  • Binding: Paperback
  • Height: 241 mm
  • Returnable: N
  • Width: 197 mm


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