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Produktbild: Intro Correspondence Analysis

Intro Correspondence Analysis

Aus der Reihe Wiley Series in Probability and Statistics

77,99 €

inkl. gesetzl. MwSt., Versandkostenfrei

Beschreibung

Produktdetails

Einband

Gebundene Ausgabe

Erscheinungsdatum

01.01.1900

Verlag

John Wiley & Sons Inc

Seitenzahl

240

Maße (L/B/H)

24,4/17/1,4 cm

Gewicht

576 g

Auflage

1. Auflage

Sprache

Englisch

ISBN

978-1-119-04194-8

Beschreibung

Produktdetails

Einband

Gebundene Ausgabe

Erscheinungsdatum

01.01.1900

Verlag

John Wiley & Sons Inc

Seitenzahl

240

Maße (L/B/H)

24,4/17/1,4 cm

Gewicht

576 g

Auflage

1. Auflage

Sprache

Englisch

ISBN

978-1-119-04194-8

Herstelleradresse

Libri GmbH
Europaallee 1
36244 Bad Hersfeld
DE

Email: gpsr@libri.de

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  • Produktbild: Intro Correspondence Analysis
  • Dedication iii
     
    Preface xi
     
    1 Introduction 1
     
    1.1 Data Visualisation 1
     
    1.2 Correspondence Analysis in a "Nutshell" 3
     
    1.3 Data Sets 4
     
    1.3.1 Traditional European Food Data 4
     
    1.3.2 Temperature Data 4
     
    1.3.3 Shoplifting Data 5
     
    1.3.4 Alligator Data 6
     
    1.4 Symmetrical vs Asymmetrical Association 7
     
    1.5 Notation 9
     
    1.5.1 The Two-way Contingency Table 9
     
    1.5.2 The Three-way Contingency Table 10
     
    1.6 Formal Test of Symmetrical Association 11
     
    1.6.1 Test of Independence for Two-way Contingency Tables 11
     
    1.6.2 The Chi-squared Statistic for a Two-way Table 12
     
    1.6.3 Analysis of the Traditional European Food Data 12
     
    1.6.4 The Chi-squared Statistic for a Three-way Table 14
     
    1.6.5 Analysis of the Alligator Data 15
     
    1.7 Formal Test of Asymmetrical Association 15
     
    1.7.1 Test of Predictability for Two-way Contingency Tables 15
     
    1.7.2 The Goodman-Kruskal tau Index 16
     
    1.7.3 Analysis of the Traditional European Food Data 17
     
    1.7.4 Test of Predictability for Three-way Contingency Tables 17
     
    1.7.5 Marcotorchino's Index 18
     
    1.7.6 Analysis of the Alligator Data 19
     
    1.7.7 The Gray-Williams Index & Delta Index 19
     
    1.8 Correspondence Analysis and R 20
     
    1.9 Overview of the Book 24
     
    Part One Classical Analysis of Two Categorical Variables 27
     
    2 Simple Correspondence Analysis 29
     
    2.1 Introduction 29
     
    2.2 Reducing Multidimensional Space 30
     
    2.2.1 Profiles Cloud of Points 30
     
    2.2.2 Profiles for the Traditional European Food Data 31
     
    2.2.3 Weighted Centred Profiles 34
     
    2.3 Measuring Symmetric Association 39
     
    2.3.1 The Pearson Ratio 39
     
    2.3.2 Analysis of the Traditional European Food Data 40
     
    2.4 Decomposing the Pearson Residual for Nominal Variables 42
     
    2.4.1 The Generalised SVD of gammaij . 1 42
     
    2.4.2 SVD of the Pearson Ratio's 44
     
    2.4.3 GSVD and the Traditional European Food Data 45
     
    2.5 Constructing a Low-Dimensional Display 45
     
    2.5.1 Standard Coordinates 45
     
    2.5.2 Principal Coordinates 47
     
    2.6 Practicalities of the Low-Dimensional Plot 51
     
    2.6.1 The Two-Dimensional Correspondence Plot 51
     
    2.6.2 What is NOT Being Shown in a Two-Dimensional Correspondence
     
    Plot? 54
     
    2.6.3 The Three-Dimensional Correspondence Plot 58
     
    2.7 The Biplot Display 58
     
    2.7.1 Definition 58
     
    2.7.2 Isometric Biplots of the Traditional European Food Data 61
     
    2.7.3 What is NOT Being Shown in a Two-Dimensional Biplot? 64
     
    2.8 The Case for No Visual Display 64
     
    2.9 Detecting Statistically Significant Points 65
     
    2.9.1 Confidence Circles and Ellipses 65
     
    2.9.2 Confidence Ellipses for the Traditional European Food Data 66
     
    2.10 Approximate P-values 70
     
    2.10.1 The Hypothesis Test and its P-value 70
     
    2.10.2 P-values and the Traditional European Food Data 71
     
    2.11 Final Comments 71
     
    3 Non-Symmetrical Correspondence Analysis 73
     
    3.1 Introduction 73
     
    3.2 Quantifying Asymmetric Association 74
     
    3.2.1 The Goodman-Kruskal tau Index 74
     
    3.2.2 The tau Index and the Traditional European Food Data 74
     
    3.2.3 Weighted Centred Column Profile 75
     
    3.2.4 Profiles of the Traditional European Food Data 75
     
    3.3 Decomposing pii|j
     
    for Nominal Variables 78
     
    3.3.1 The Generalised SVD of pii|j 78
     
    3.3.2 GSVD and the Traditional Food Data 7