"Like good writing, producing an effective graphical display requires an understanding of purpose - what is to be communicated, and to whom." (Michael Friendly, "Gallery of Data Visualization", 1991)
"It is common to think of statistical graphics and data visualization as relatively modern developments in statistics. In fact, the graphic representation of quantitative information has deep roots. These roots reach into the histories of the earliest map-making and visual depiction, and later into thematic cartography, statistics and statistical graphics, medicine, and other fields. Along the way, developments in technologies (printing, reproduction) mathematical theory and practice, and empirical observation and recording, enabled the wider use of graphics and new advances in form and content." (Michael Friendly. "A brief history of data visualization", 2006)
"The graphic portrayal of quantitative information has deep roots. These roots reach into histories of thematic cartography, statistical graphics, and data visualization, which are intertwined with each other." (Michael Friendly. "Milestones in the history of thematic cartography, statistical graphics, and data visualization", 2008)
"Algorithmic calculation can give only pseudo-random numbers, but some methods come closer than others in behaving like quantities that are truly random, such as numbers obtained from tossing a very large number of dice." (Michael Friendly. "Milestones in the history of thematic cartography, statistical graphics, and data visualization", 2008)
"But to a ballet dancer, the art is in getting all the body parts to do those things in sync with a musical score to tell a wordless story of emotion entirely through change in position over time. In data visualization, as in physics and ballet, motion is a manifestation of the relation between time and space, and so the recording and display of motion added time as a fourth dimension to the abstract world of data." (Michael Friendly. "Milestones in the history of thematic cartography, statistical graphics, and data visualization", 2008)
"Correlation does not imply causation: often some other missing third variable is influencing both of the variables you are correlating. […] The need for a scatterplot arose when scientists had to examine bivariate relations between distinct variables directly. As opposed to other graphic forms - pie charts, line graphs, and bar charts - the scatterplot offered a unique advantage: the possibility to discover regularity in empirical data (shown as points) by adding smoothed lines or curves designed to pass 'not through, but among them', so as to pass from raw data to a theory-based description, analysis, and understanding." (Michael Friendly & Howard Wainer, "A History of Data Visualization and Graphic Communication", 2021)
"However, just as in cooking, the details matter: the wrong spice can ruin the stew. In graphing data, different methods or graphical features can make it easier or harder to perceive and understand relationships or comparisons from the same data." (Michael Friendly & Howard Wainer, "A History of Data Visualization and Graphic Communication", 2021)
"Indeed, among all forms of statistical graphics, the scatterplot may be considered the most versatile and generally useful invention in the entire history of statistical graphics. Essential characteristics of a scatterplot are that two quantitative variables are measured on the same observational units (workers); the values are plotted as points referred to perpendicular axes; and the goal is to show something about the relation between these variables, typically how the ordinate variable, y, varies with the abscissa variable, x." (Michael Friendly & Howard Wainer, "A History of Data Visualization and Graphic Communication", 2021)
"Its primary function was to make previously invisible phenomena subject to direct inspection in a graphic display […] The graphic method had another function, that of communication to the scientific community and educated readers. These displays made complex phenomena palpable and concrete." (Michael Friendly & Howard Wainer, "A History of Data Visualization and Graphic Communication", 2021)
"Our central questions in this book are 'How did the graphic depiction of numbers arise?' and more importantly, 'Why?' What led to the key innovations in graphs and diagrams that are commonplace today? What were the circumstances or scientific problems that made visual depiction more useful than mere words and numbers? Finally, how did these graphic inventions make a difference in comprehending natural and social phenomena and communicating that understanding?" (Michael Friendly & Howard Wainer, "A History of Data Visualization and Graphic Communication", 2021)
"[...] scatterplots had advantages over earlier graphic forms: the ability to see clusters, patterns, trends, and relations in a cloud of points. Perhaps most importantly, it allowed the addition of visual annotations (point symbols, lines, curves, enclosing contours, etc.) to make those relationships more coherent and tell more nuanced stories." (Michael Friendly & Howard Wainer, "A History of Data Visualization and Graphic Communication", 2021)
"The general principles of starting with a well-defined question, engaging in careful observation, and then formulating hypotheses and assessing the strength of evidence for and against them became known as the scientific method." (Michael Friendly & Howard Wainer, "A History of Data Visualization and Graphic Communication", 2021)
"The plotting of real data had a remarkable, and largely unanticipated, benefit. It often forced viewers to see what they hadn’t expected. The frequency with which this happened gave birth to the empirical modern approach to science which welcomes the plotting of observed data values with the goal of investigating suggestive patterns." (Michael Friendly & Howard Wainer, "A History of Data Visualization and Graphic Communication", 2021)
"Visual displays of empirical information are too often thought to be just compact summaries that, at their best, can clarify a muddled situation. This is partially true, as far as it goes, but it omits the magic. […] sometimes, albeit too rarely, the combination of critical questions addressed by important data and illuminated by evocative displays can achieve a transcendent, and often wholly unexpected, result. At their best, visualizations can communicate emotions and feelings in addition to cold, hard facts." (Michael Friendly. "Milestones in the history of thematic cartography, statistical graphics, and data visualization", 2008)
"We are accustomed to intellectual diffusion taking place from the natural and physical sciences into the social sciences; certainly that is the direction taken for both calculus and the scientific method. But statistical graphics in particular, and statistics in general, took the reverse route." (Michael Friendly & Howard Wainer, "A History of Data Visualization and Graphic Communication", 2021)
"We live on islands surrounded by seas of data. Some call it 'big data'. In these seas live various species of observable phenomena. Ideas, hypotheses, explanations, and graphics also roam in the seas of data and can clarify the waters or allow unsupported species to die. These creatures thrive on visual explanation and scientific proof. Over time new varieties of graphical species arise, prompted by new problems and inner visions of the fishers in the seas of data." (Michael Friendly & Howard Wainer, "A History of Data Visualization and Graphic Communication", 2021)
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