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In "Visualization Analysis and Design" Tamara Munzner writes "Computer-based visualization systems provide visual representations of datasets designed to help people carry out tasks more effectively." Munzner agues that visualization "is suitable when there is a need to augment human capabilities rather than replace people with computational ...
Data visualization is a related subcategory of visualization dealing with statistical graphics and geospatial data (as in thematic cartography) that is abstracted in schematic form. [ 7 ] Information visualization concentrates on the use of computer-supported tools to explore large amount of abstract data.
Dramatic visualization: Representing an object or character with abundant descriptive detail, or mimetically rendering gestures and dialogue to make a scene more visual or imaginatively present to an audience. This technique appears at least as far back as the Arabian Nights. [13] Euphuism: An artificial, highly elaborate way of writing or ...
Therefore, it is crucial to identify the appropriate visualization for the data set and infographic by taking into consideration graphical features such as position, size, shape, and color. There are primarily five types of visualization categories – time-series data, statistical distributions, maps, hierarchies, and networking. [3]
Spatial visualization ability is the ability to manipulate mentally two- and three-dimensional figures. [ 1 ] Spatial-temporal reasoning is prominent among visual thinkers as well as among kinesthetic learners (those who learn through movement, physical patterning and doing) and logical thinkers (mathematical thinkers who think in patterns and ...
Visual analytics is "the science of analytical reasoning facilitated by interactive visual interfaces." [2] It can attack certain problems whose size, complexity, and need for closely coupled human and machine analysis may make them otherwise intractable. [3]
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Exploratory data analysis is an analysis technique to analyze and investigate the data set and summarize the main characteristics of the dataset. Main advantage of EDA is providing the data visualization of data after conducting the analysis.