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Introduction | |
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Methodology | |
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Organisation of the data | |
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Statistical units and statistical variables | |
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Data matrices and their transformations | |
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Complex data structures | |
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Summary | |
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Summary statistics | |
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Univariate exploratory analysis | |
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Measures of location | |
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Measures of variability | |
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Measures of heterogeneity | |
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Measures of concentration | |
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Measures of asymmetry | |
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Measures of kurtosis | |
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Bivariate exploratory analysis of quantitative data | |
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Multivariate exploratory analysis of quantitative data | |
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Multivariate exploratory analysis of qualitative data | |
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Independence and association | |
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Distance measures | |
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Dependency measures | |
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Model-based measures | |
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Reduction of dimensionality | |
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Interpretation of the principal components | |
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Further reading | |
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Model specification | |
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Measures of distance | |
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Euclidean distance | |
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Similarity measures | |
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Multidimensional scaling | |
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Cluster analysis | |
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Hierarchical methods | |
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Evaluation of hierarchical methods | |
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Non-hierarchical methods | |
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Linear regression | |
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Bivariate linear regression | |
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Properties of the residuals | |
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Goodness of fit | |
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Multiple linear regression | |
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Logistic regression | |
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Interpretation of logistic regression | |
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Discriminant analysis | |
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Tree models | |
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Division criteria | |
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Pruning | |
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Neural networks | |
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Architecture of a neural network | |
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The multilayer perceptron | |
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Kohonen networks | |
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Nearest-neighbour models | |
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Local models | |
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Association rules | |
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Retrieval by content | |
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Uncertainty measures and inference | |
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Probability | |
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Statistical models | |
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Statistical inference | |
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Non-parametric modelling | |
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The normal linear model | |
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Main inferential results | |
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Generalised linear models | |
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The exponential family | |
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Definition of generalised linear models | |
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The logistic regression model | |
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Log-linear models | |
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Construction of a log-linear model | |
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Interpretation of a log-linear model | |
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Graphical log-linear models | |
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Log-linear model comparison | |
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Graphical models | |
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Symmetric graphical models | |
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Recursive graphical models | |
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Graphical models and neural networks | |
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Survival analysis models | |
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Further reading | |
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Model evaluation | |
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Criteria based on statistical tests | |
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Distance between statistical models | |
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Discrepancy of a statistical model | |
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Kullback-Leibler discrepancy | |
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Criteria based on scoring functions | |
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Bayesian criteria | |
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Computational criteria | |
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Criteria based on loss functions | |
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Further reading | |
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Business case studies | |
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Describing website visitors | |
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Objectives of the analysis | |
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Description of the data | |
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Exploratory analysis | |
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Model building | |
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Cluster analysis | |
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Kohonen networks | |
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Model comparison | |
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Summary report | |
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Market basket analysis | |
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Objectives of the analysis | |
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Description of the data | |
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Exploratory data analysis | |
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Model building | |
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Log-linear models | |
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Association rules | |
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Model comparison | |
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Summary report | |
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Describing customer satisfaction | |
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Objectives of the analysis | |
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Description of the data | |
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Exploratory data analysis | |
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Model building | |
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Summary | |
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Predicting credit risk of small businesses | |
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Objectives of the analysis | |
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Description of the data | |
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Exploratory data analysis | |
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Model building | |
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Model comparison | |
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Summary report | |
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Predicting e-learning student performance | |
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Objectives of the analysis | |
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Description of the data | |
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Exploratory data analysis | |
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Model specification | |
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Model comparison | |
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Summary report | |
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Predicting customer lifetime value | |
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Objectives of the analysis | |
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Description of the data | |
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Exploratory data analysis | |
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Model specification | |
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Model comparison | |
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Summary report | |
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Operational risk management | |
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Context and objectives of the analysis | |
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Exploratory data analysis | |
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Model building | |
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Model comparison | |
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Summary conclusions | |
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References | |
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Index | |