Graphical and numerical descriptive analysis: Exploratory tools applied to Vietnamese data

Multivariate exploratory tools for microarray data analysis.

The ultimate success of microarray technology in basic and applied biological sciences depends critically on the development of statistical methods for gene expression data analysis. The most widely used tests for differential expression of genes are essentially univariate. Such tests disregard the multidimensional structure of microarray data. Multivariate methods are needed to utilize the inf...

Tutorial 2: Descriptive Statistics and Exploratory Data Analysis

1 Univariate Statistics and Histograms . . . . . . . . . . . . . . . . . . 2 1.1 Measures of Location . . . . . . . . . . . . . . . . . . . . . . . 3 1.2 Measures of Position . . . . . . . . . . . . . . . . . . . . . . . 5 1.3 Measures of Dispersion . . . . . . . . . . . . . . . . . . . . . . 7 2 Comparing the Distributions of Datasets . . . . . . . . . . . . . . . . 8 2.1 Comparing Empirical a...

Nonlinear Exploratory Data Analysis Applied to Seismic Signals

This paper compares three unsupervised projection methods: Principal Component Analysis (PCA), which is linear, Self-Organizing Map (SOM) and Curvilinear Component Analysis (CCA), which are both nonlinear. Performance comparison of the three methods is made on a set of seismic data recorded on Stromboli that includes three classes of signals: explosion-quakes, landslides, and microtremors. The ...

Graphical Methods for Exploratory Multivariate Longitudinal Data Analysis

This paper describes direct manipulation and dynamic graphics for analyzing multivariate longitudinal data. Longitudinal data measures individuals repeatedly in time, perhaps at irregular and unequal time points. There is an emphasis on studying the individual patterns as well as mean trends because we can. Static plots of individuals are messy and often unreadable because there are many overla...

Applied and Numerical Harmonic Analysis