Data Visualization

Introduction

Graphics are crucial for displaying results and offer a great way to explore data. Presentation graphics have received a lot of attention, especially since Edward Tute's excellent books. But rather than being articulated in formal theories, this knowledge is expressed in guidelines to be adhered to. Although Bertin's 1960s work is frequently referenced, it hasn't been expanded upon. This is a peculiar situation. Given the wide range of applications for graphics, one would think that theoretical advancements would have been more prevalent.

Practical vs. Theoretical Literature

In science, there are instances where a subject has a large body of theoretical literature but minimal practical literature. In practically every issue of every scientific magazine that deals with quantitative analysis, there are several examples. Occasionally, essays about particular graphical forms are published in a more theoretical style, but not much else. This could be due to the fact that publishing research on a technical computational challenge is simpler than publishing work on enhancing a graphic display.

Forms and Applications of Graphics

In both form and application, presentation graphics and exploration graphics differ from one another. These displays ought to be of excellent quality and provide thorough explanations and definitions of the variables displayed as well as the graphic's format. Similar to mathematical theorem proofs, presentation graphics should provide compelling evidence for their conclusions, even if they don't reveal the methodology used to get at them.

There are a lot of things that can be used, and they should be quick and informative instead of sluggish and accurate. There is no need for intricate legends and captions because they are not meant for display. While thousands of exploratory graphics might be created to support an analyst's data investigations, a single presentation graphic will be created for thousands of readers to examine.

Evolution Through Technology

In recent years, graphics have greatly benefited from advances in processing power. It is now quite easy to develop intricate, accurate displays and print them at high resolution with remarkable quality. In the beginning, computers were more of a drawback for visuals, although that was not always the case. At best, computer screens and printers could create awkward, low-resolution, colourless line-driven displays. These were no match for meticulous, hand-drawn displays.

Furthermore, even the first computers enabled the fitting of increasingly complex models and greatly simplified numerous calculations. Graphics have only regained their prominence in the last 20 years as a result of this shift in focus.

Presentation vs. Exploratory Graphics

Presentation graphics, or graphics created to illustrate and explain outcomes, are the subject of these remarks. Exploratory graphics—that is, graphics created to facilitate data exploration—have benefited greatly from advancements in computing. Both the amount and the quality of graphic representation have increased. Drawing numerous displays of the same data or interactively browsing through numerous versions to find information in the data is now simple. Only slowly are these qualities being recognised and utilised.

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The Role of Software in Visualization

Future scientific historians will find it intriguing to investigate the significance of software availability and popularity in influencing the types of analyses conducted and the way they are presented. Excel is a spreadsheet that seems to be indispensable in the business sector. A specific graphic form will not be used if Excel does not provide it. Excel and its features are also used by many scientists, even though they hardly ever need access to computing power.

For a long time, SAS and SPSS were the most popular software packages in the statistics field. While all of these packages are gradually moving in that direction and increasing the variety and adaptability of the presentation graphics they offer, none of them currently offer useful interactive capabilities for exploratory graphics.

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The Rise of Data Visualization and Its Meaning

The word "data visualisation" is new. It conveys the notion that it entails more than only graphically portraying data. A good presentation should also make the information behind the data visible; the visual should help viewers or readers understand the data's structure.

The emerging field of information visualisation is associated with the term data visualisation. This is closely related to computer scientist research and involves the visualisation of various types of information, not only data. Until now, research in this field has tended to focus just on providing information, not on what may be inferred from it.

Statisticians typically focus on the statistical characteristics of outcomes and are more interested in variability. This can be made clearer by tying visuals and statistical modelling together more closely. This is a promising line of inquiry made possible by the adaptability of modern computer software. This is when statisticians come in handy.