Maciejewski R. Data Representations, Transformations, and Statistics for Visual Reasoning

N.-Y.: Morgan & Claypool Publishers, 2011. - 87p.Analytical reasoning techniques are methods by which users explore their data to obtain insight and knowledge that can directly support situational awareness and decision making. Recently, the analytical reasoning process has been augmented through the use of interactive visual representations and tools which utilize cognitive, design and perceptual principles. These tools are commonly referred to as visual analytics tools, and the underlying methods and principles have roots in a variety of disciplines. This chapter provides an introduction to young researchers as an overview of common visual representations and statistical analysis methods utilized in a variety of visual analytics systems. The application and design of visualization and analytical algorithms are subject to design decisions, parameter choices, and many conflicting requirements. As such, this chapter attempts to provide an initial set of guidelines for the creation of the visual representation, including pitfalls and areas where the graphics can be enhanced through interactive exploration. Basic analytical methods are explored as a means of enhancing the visual analysis process, moving from visual analysis to visual analytics.Data Types
Ordinal Data
Ratio Data
Design Principles for Color Schemes
Sequential Color Scales
Mutlivariate Color Schemes
Choosing a Color Scheme
Data Preconditioning
Determining Bin Widths
Increasing the Dimensionality of a Histogram
Kernel Density Estimation
Multivariate Visualization Techniques
Scatterplots and Scatterplot Matrices
Parallel Coordinate Plots
Abstract Multivariate Visualizations
Principal Component Analysis
K-Means Clustering
Multi-dimensional Scaling
Self-Organizing Maps
Line Graphs
Calendar View
Multivariate Temporal Exploration
Animation
Control Charts
Time Series Modeling
Geographic Visualization
Dasymetric Maps
Isopleth Maps
Class Interval Selection
Animating Maps
Spatial Autocorrelation
Local Indicators of Spatial Association
AMOEBA Clustering
Spatial Scan StatisticsAuthor's Biography