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20030526000200.0 |
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971112s1998 caua b 001 0 eng |
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|a 97047133
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|a 0534237967
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|a (NhCcYBP)YBT 97047133
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|a (NhCcYBP)YBP98138162152
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|a DLC
|c DLC
|d DLC
|d OrLoB-B
|d OCoLC
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|a QA278
|b .J615 1998
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|a 519.5/35
|2 21
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|a Johnson, Dallas E.,
|d 1938-
|0 http://id.loc.gov/authorities/names/n82232858
|1 http://viaf.org/viaf/84497873
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| 245 |
1 |
0 |
|a Applied multivariate methods for data analysts /
|c Dallas E. Johnson.
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| 260 |
|
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|a Pacific Grove, Calif. :
|b Duxbury Press,
|c c1998.
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| 300 |
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|a xiv, 567 p. :
|b ill. ;
|c 25 cm. +
|e 1 computer disk (3 1/2 in.)
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| 336 |
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|a text
|b txt
|2 rdacontent
|0 http://id.loc.gov/vocabulary/contentTypes/txt
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| 337 |
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|a unmediated
|b n
|2 rdamedia
|0 http://id.loc.gov/vocabulary/mediaTypes/n
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| 338 |
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|a volume
|b nc
|2 rdacarrier
|0 http://id.loc.gov/vocabulary/carriers/nc
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| 504 |
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|a Includes bibliographical references (p. 555-562) and index.
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| 505 |
0 |
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|g 1.
|t Applied Multivariate Methods.
|g 1.1.
|t An Overview of Multivariate Methods.
|g 1.2.
|t Two Examples.
|g 1.3.
|t Types of Variables.
|g 1.4.
|t Data Matrices and Vectors.
|g 1.5.
|t The Multivariate Normal Distribution.
|g 1.6.
|t Statistical Computing.
|g 1.7.
|t Multivariate Outliers.
|g 1.8.
|t Multivariate Summary Statistics.
|g 1.9.
|t Standardized Data and/or Z Scores --
|g 2.
|t Sample Correlations.
|g 2.1.
|t Statistical Tests and Confidence Intervals.
|g 2.2.
|t Summary --
|g 3.
|t Multivariate Data Plots.
|g 3.1.
|t Three-Dimensional Data Plots.
|g 3.2.
|t Plots of Higher Dimensional Data.
|g 3.3.
|t Plotting to Check for Multivariate Normality --
|g 4.
|t Eigenvalues and Eigenvectors.
|g 4.1.
|t Trace and Determinant.
|g 4.2.
|t Eigenvalues.
|g 4.3.
|t Eigenvectors.
|g 4.4.
|t Geometric Descriptions (p = 2).
|g 4.5.
|t Geometric Descriptions (p = 3).
|g 4.6.
|t Geometric Descriptions (p > 3) --
|g 5.
|t Principal Components Analysis.
|g 5.1.
|t Reasons for Using Principal Components Analysis.
|g 5.2.
|t Objectives of Principal Components Analysis.
|g 5.3.
|t Principal Components Analysis on the Variance-Covariance Matrix [Sigma].
|g 5.4.
|t Estimation of Principal Components.
|g 5.5.
|t Determining the Number of Principal Components.
|g 5.6.
|t Caveats.
|g 5.7.
|t PCA on the Correlation Matrix P.
|g 5.8.
|t Testing for Independence of the Original Variables.
|g 5.9.
|t Structural Relationships.
|g 5.10.
|t Statistical Computing Packages --
|g 6.
|t Factor Analysis.
|g 6.1.
|t Objectives of Factor Analysis.
|g 6.2.
|t Caveats.
|g 6.3.
|t Some History of Factor Analysis.
|g 6.4.
|t The Factor Analysis Model.
|g 6.5.
|t Factor Analysis Equations.
|g 6.6.
|t Solving the Factor Analysis Equations.
|g 6.7.
|t Choosing the Appropriate Number of Factors.
|g 6.8.
|t Computer Solutions of the Factor Analysis Equations.
|g 6.9.
|t Rotating Factors.
|g 6.10.
|t Oblique Rotation Methods.
|g 6.11.
|t Factor Scores --
|g 7.
|t Discriminant Analysis.
|g 7.1.
|t Discrimination for Two Multivariate Normal Populations.
|g 7.2.
|t Cost Functions and Prior Probabilities (Two Populations).
|g 7.3.
|t A General Discriminant Rule (Two Populations).
|g 7.4.
|t Discriminant Rules (More than Two Populations).
|g 7.5.
|t Variable Selection Procedures.
|g 7.6.
|t Canonical Discriminant Functions.
|g 7.7.
|t Nearest Neighbor Discriminant Analysis.
|g 7.8.
|t Classification Trees --
|g 8.
|t Logistic Regression Methods.
|g 8.1.
|t Logistic Regression Model.
|g 8.2.
|t The Logit Transformation.
|g 8.3.
|t Variable Selection Methods.
|g 8.4.
|t Logistic Discriminant Analysis (More Than Two Populations) --
|g 9.
|t Cluster Analysis.
|g 9.1.
|t Measures of Similarity and Dissimilarity.
|g 9.2.
|t Graphical Aids in Clustering.
|g 9.3.
|t Clustering Methods.
|g 9.4.
|t Multidimensional Scaling --
|g 10.
|t Mean Vectors and Variance-Covariance Matrices.
|g 10.1.
|t Inference Procedures for Variance-Covariance Matrices.
|g 10.2.
|t Inference Procedures for a Mean Vector.
|g 10.3.
|t Two Sample Procedures.
|g 10.4.
|t Profile Analyses.
|g 10.5.
|t Additional Two-Group Analyses --
|g 11.
|t Multivariate Analysis of Variance.
|g 11.1.
|t MANOVA.
|g 11.2.
|t Dimensionality of the Alternative Hypothesis.
|g 11.3.
|t Canonical Variates Analysis.
|g 11.4.
|t Confidence Regions for Canonical Variates --
|g 12.
|t Prediction Models and Multivariate Regression.
|g 12.1.
|t Multiple Regression.
|g 12.2.
|t Canonical Correlation Analysis.
|g 12.3.
|t Factor Analysis and Regression.
|g App. A.
|t Matrix Results --
|g App. B.
|t Work Attitudes Survey --
|g App. C.
|t Family Control Study.
|
| 538 |
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|a System requirements for accompanying computer disk: IBM PC or compatible.
|
| 650 |
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0 |
|a Multivariate analysis.
|0 http://id.loc.gov/authorities/subjects/sh85088390
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| 650 |
|
7 |
|a Multivariate analysis.
|2 fast
|0 http://id.worldcat.org/fast/fst01029105
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| 901 |
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|a ToCBNA
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| 903 |
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|a HeVa
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| 903 |
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|a Hathi
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| 035 |
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|a (OCoLC)37993084
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|t Library of Congress classification
|a QA278.J615 1998
|l JCL
|c JCL-Sci
|i 3956348
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| 927 |
|
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|t Library of Congress classification
|a QA278.J615 1998
|v text
|l JCL
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|i 5501203
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