"Since a table is a collection of certain sets of data, a chart with one curve representing each set of data can be made to take the place of the table. Wherever a chart can be plotted by straight lines, the speed of this is infinitely greater than making out a table, and where the curvilinear law is known, or can be approximated by the use of the empiric law, the speed is but little less." (Allan C Haskell, "How to Make and Use Graphic Charts", 1919)
"For many purposes graphical accuracy is sufficient. The speed of graphical processes, and more especially the advantages of visual presentation in pointing out facts or clues which might otherwise be overlooked, make graphical analysis very valuable." (Frederick Mosteller & John W Tukey, "The Uses and Usefulness of Binomial Probability Paper?", Journal of the American Statistical Association 44, 1949)
"Since the chief purpose of the nomogram is to make exact data available for operational use, its chief competitor is the table. Operational tables may break Ehrenberg's two-digit rule, since they are not used to detect general trends but to provide exact data for some operational purpose. The choice between nomogram and table involves a complex tradeoff among cost, space, convenience, accuracy, and speed. These tradeoff situations provide one good reason why no one graphic format is suitable for all purposes. Of course, there can be good methods (sarisfying solutions) for particular cases." (Michael Macdonald-Ross, "Graphics in Texts", Review of Research in Education Vol. 5, 1977)
"The ease and speed with which tables can be understood depends very much on the tabulation logic. The author must ask himself what information the reader already has when he consults a particular table, and what information he is seeking from it. The row and column headings should relate to the information he already has, thus leading him to the information he seeks which is displayed in the body of the table." (Linda Reynolds & Doig Simmonds, "Presentation of Data in Science" 4th Ed, 1984)
"There are some who argue that a graph is a success only if the important information in the data can be seen within a few seconds. While there is a place for rapidly-understood graphs, it is too limiting to make speed a requirement in science and technology, where the use of graphs ranges from, detailed, in-depth data analysis to quick presentation." (William S Cleveland, "The Elements of Graphing Data", 1985)
"Working with binned data directly addresses large data set issues of computation and plotting speed. Almost everything that can bc done with the original data can be done faster with binned data. Further, working with binned data allows image processing algorithms to be adapted and applied to bin cells. Thus tools can bc brought to bare that are not traditionally associated with exploratory data analysis." (Daniel B Carr, "Looking at Large Data Sets Using Binned Data Plots", [in "Computing and Graphics in Statistics"] 1991)
"In general. statistical graphics should be moderately greater in length than in height. And, as William Cleveland discovered, for judging slopes and velocities up and down the hills in time-series, best is an aspect ratio that yields hill - slopes averaging 45°, over every cycle in the time-series. Variations in slopes are best detected when the slopes are around 45°, uphill or downhill." (Edward R Tufte, "Beautiful Evidence", 2006)
"Sparklines are wordlike graphics, With an intensity of visual distinctions comparable to words and letters. [...] Words visually present both an overall shape and letter-by-letter detail; since most readers have seen the word previously, the visual task is usually one of quick recognition. Sparklines present an overall shape and aggregate pattern along with plenty of local detail. Sparklines are read the same way as words, although much more carefully and slowly." (Edward R Tufte, "Beautiful Evidence", 2006)
"The biggest difference between line graphs and sparklines is that a sparkline is compact with no grid lines. It isnʼt meant to give precise values; rather, it should be considered just like any other word in the sentence. Its general shape acts as another term and lends additional meaning in its context. The driving forces behind these compact sparklines are speed and convenience." (Brian Suda, "A Practical Guide to Designing with Data", 2010)
"As a first principle, any visualization should convey its information quickly and easily, and with minimal scope for misunderstanding. Unnecessary visual clutter makes more work for the reader’s brain to do, slows down the understanding" (at which point they may give up) and may even allow some incorrect interpretations to creep in." (Robert Grant, "Data Visualization: Charts, Maps and Interactive Graphics", 2019)
"The way we explore data today, we often aren't constrained by rigid hypothesis testing or statistical rigor that can slow down the process to a crawl. But we need to be careful with this rapid pace of exploration, too. Modern business intelligence and analytics tools allow us to do so much with data so quickly that it can be easy to fall into a pitfall by creating a chart that misleads us in the early stages of the process." (Ben Jones, "Avoiding Data Pitfalls: How to Steer Clear of Common Blunders When Working with Data and Presenting Analysis and Visualizations", 2020)
