📉Graphical Representation: Column Charts (Just the Quotes)

"First, it is generally inadvisable to attempt to portray a series of more than four or five categories by means of pie charts. If, for example, there are six, eight, or more categories, it may be very confusing to differentiate the relative values portrayed, especially if several small sectors are of approximately the same size. Second, the pie chart may lose its effectiveness if an attempt is made to compare the component values of several circles, as might be found in a temporal or geographical series. In such case the one-hundred percent bar or column chart is more appropriate. Third, although the proportionate values portrayed in a pie chart are measured as distances along arcs about the circle, actually there is a tendency to estimate values in terms of areas of sectors or by the size of subtended angles at the center of the circle." (Calvin F Schmid, "Handbook of Graphic Presentation", 1954)

"The types of graphics used in operating a business fall into three main categories: diagrams, maps, and charts. Diagrams, such as organization diagrams, flow diagrams, and networks, are usually intended to graphically portray how an activity should be, or is being, accomplished, and who is responsible for that accomplishment. Maps such as route maps, location maps, and density maps, illustrate where an activity is, or should be, taking place, and what exists there. [...] Charts such as line charts, column charts, and surface charts, are normally constructed to show the businessman how much and when. Charts have the ability to graphically display the past, present, and anticipated future of an activity. They can be plotted so as to indicate the current direction that is being followed in relationship to what should be followed. They can indicate problems and potential problems, hopefully in time for constructive corrective action to be taken." (Robert D Carlsen & Donald L Vest, "Encyclopedia of Business Charts", 1977)

"The bar or column chart is the easiest type of graphic to prepare and use in reports. It employs a simple form: four straight lines that are joined to construct a rectangle or oblong box. When the box is shown horizontally it is called a bar; when it is shown vertically it is called a column. [...] The bar chart is an effective way to show comparisons between or among two or more items. It has the added advantage of being easily understood by readers who have little or no background in statistics and who are not accustomed to reading complex tables or charts." (Robert Lefferts, "Elements of Graphics: How to prepare charts and graphs for effective reports", 1981)

"The bar graph and the column graph are popular because they are simple and easy to read. These are the most versatile of the graph forms. They can be used to display time series, to display the relationship between two items, to make a comparison among several items, and to make a comparison between parts and the whole (total). They do not appear to be as 'statistical', which is an advantage to those people who have negative attitudes toward statistics. The column graph shows values over time, and the bar graph shows values at a point in time. bar graph compares different items as of a specific time (not over time)." (Anker V Andersen, "Graphing Financial Information: How accountants can use graphs to communicate", 1983)

"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)

"The space between columns, on the other hand, should be just sufficient to separate them clearly, but no more. The columns should not, under any circumstances, be spread out merely to fill the width of the type area. […] Sometimes, however, it is difficult to avoid undesirably large gaps between columns, particularly where the data within any given column vary considerably in length. This problem can sometimes be solved by reversing the order of the columns […]. In other instances the insertion of additional space after every fifth entry or row can be helpful, […] but care must be taken not to imply that the grouping has any special meaning." (Linda Reynolds & Doig Simmonds, "Presentation of Data in Science" 4th Ed, 1984)

"There are some chart types that occasionally appear in print but are so bad that they serve neither honesty nor deceit. Among these monuments to human ingenuity at the expense of common sense are the concentric donut and overlapping segments. The concentric donut is really just a bar or column chart bent back on itself to save space. However as anyone who has ever watched a two or four hundred metre race will know, to make sense of the order of arrival at the tape you have to stagger the start to take account of the bend in the track. Blithely ignoring this problem, the concentric donut uses to diminish the difference between the inner and the outer absolute values by anything up to 2.5 times." (Nicholas Strange, "Smoke and Mirrors: How to bend facts and figures to your advantage", 2007)

"We tend automatically to think of all the categories represented on the horizontal axis of a column Chart as being equally important. They vary of course on the value axis. Otherwise, there would be little point in the chart, but there is somehow this feeling that they are in other respects similar members of a group. This convention can be put to good use to manipulate the message of the most boring bar or column chart." (Nicholas Strange, "Smoke and Mirrors: How to bend facts and figures to your advantage", 2007)

"Visualizations that use different lengths of rectangles to show quantities are called bar charts. The rectangles in bar charts are called bars, and each bar represents a single category from a categorical variable. [...] When the bars in a bar chart are standing up, these visualizations are sometimes called column charts. Column charts and bar charts work in exactly the same way, but you might choose one over the other to fit better on a page or because it suits the data better." (Nancy Organ, "Data Visualization for People of All Ages", 2024)

📉Graphical Representation: Diagramming (Just the Quotes)

"Diagrams are of great utility for illustrating certain questions of vital statistics by conveying ideas on the subject through the eye, which cannot be so readily grasped when contained in figures." (Florence Nightingale, "Mortality of the British Army", 1857)

"They [diagrams] are designed not so much to allow of reference to particular numbers, which can be better had from printed tables of figures, as to exhibit to the eye the general results of large masses of figures which it is hopeless to attack in any other way than by graphical representation." (William S Jevons, [letter to Richard Hutton] 1863)

"[…] deduction consists in constructing an icon or diagram the relations of whose parts shall present a complete analogy with those of the parts of the object of reasoning, of experimenting upon this image in the imagination, and of observing the result so as to discover unnoticed and hidden relations among the parts." (Charles S Peirce, 1885)

"Deduction is that mode of reasoning which examines the state of things asserted in the premises, forms a diagram of that state of things, perceives in the parts of the diagram relations not explicitly mentioned in the premises, satisfies itself by mental experiments upon the diagram that these relations would always subsist, or at least would do so in a certain proportion of cases, and concludes their necessary, or probable, truth." (Charles S Peirce, "Kinds of Reasoning", cca. 1896)

"The preliminary examination of most data is facilitated by the use of diagrams. Diagrams prove nothing, but bring outstanding features readily to the eye; they are therefore no substitutes for such critical tests as may be applied to the data, but are valuable in suggesting such tests, and in explaining the conclusions founded upon them." (Sir Ronald A Fisher, "Statistical Methods for Research Workers", 1925)

"Although, the tabular arrangement is the fundamental form for presenting a statistical series, a graphic representation - in a chart or diagram - is often of great aid in the study and reporting of statistical facts. Moreover, sometimes statistical data must be taken, in their sources, from graphic rather than tabular records." (William L Crum et al, "Introduction to Economic Statistics", 1938)

"The eye can accurately appraise only very few features of a diagram, and consequently a complicated or confusing diagram will lead the reader astray. The fundamental rule for all charting is to use a plan which is simple and which takes account, in its arrangement of the facts to be presented, of the above-mentioned capacities of the eye."  (William L Crum et al, "Introduction to Economic Statistics", 1938)

"[…] statistical literacy. That is, the ability to read diagrams and maps; a 'consumer' understanding of common statistical terms, as average, percent, dispersion, correlation, and index number."  (Douglas Scates, "Statistics: The Mathematics for Social Problems", 1943)

"I believe, that the decisive idea which brings the solution of a problem is rather often connected with a well-turned word or sentence. The word or the sentence enlightens the situation, gives things, as you say, a physiognomy. It can precede by little the decisive idea or follow on it immediately; perhaps, it arises at the same time as the decisive idea. […]  The right word, the subtly appropriate word, helps us to recall the mathematical idea, perhaps less completely and less objectively than a diagram or a mathematical notation, but in an analogous way. […] It may contribute to fix it in the mind." (George Pólya [in a letter to Jaque Hadamard, "The Psychology of Invention in the Mathematical Field", 1949])

"The primary purpose of a graph is to show diagrammatically how the values of one of two linked variables change with those of the other. One of the most useful applications of the graph occurs in connection with the representation of statistical data." (John F Kenney & E S Keeping, "Mathematics of Statistics" Vol. I 3rd Ed., 1954)

"A model is a qualitative or quantitative representation of a process or endeavor that shows the effects of those factors which are significant for the purposes being considered. A model may be pictorial, descriptive, qualitative, or generally approximate in nature; or it may be mathematical and quantitative in nature and reasonably precise. It is important that effective means for modeling be understood such as analog, stochastic, procedural, scheduling, flow chart, schematic, and block diagrams." (Harold Chestnut, "Systems Engineering Tools", 1965)

"To analyse graphic representation precisely, it is helpful to distinguish it from musical, verbal and mathematical notations, all of which are perceived in a linear or temporal sequence. The graphic image also differs from figurative representation essentially polysemic, and from the animated image, governed by the laws of cinematographic time. Within the boundaries of graphics fall the fields of networks, diagrams and maps. The domain of graphic imagery ranges from the depiction of atomic structures to the representation of galaxies and extends into the spheres of topography and cartography." (Jacques Bertin, "Semiology of graphics" ["Semiologie Graphique"], 1967)

"One of the methods making the data intelligible is to represent it by means of graphs and diagrams. The graphic & diagrammatic representation of the data is always appealing to the eye as well as to the mind of the observer." (S P Singh & R P S Verma, "Agricultural Statistics", cca. 1969)

"Pencil and paper for construction of distributions, scatter diagrams, and run-charts to compare small groups and to detect trends are more efficient methods of estimation than statistical inference that depends on variances and standard errors, as the simple techniques preserve the information in the original data." (William E Deming, "On Probability as Basis for Action" American Statistician Vol. 29 (4), 1975)

"The types of graphics used in operating a business fall into three main categories: diagrams, maps, and charts. Diagrams, such as organization diagrams, flow diagrams, and networks, are usually intended to graphically portray how an activity should be, or is being, accomplished, and who is responsible for that accomplishment. Maps such as route maps, location maps, and density maps, illustrate where an activity is, or should be, taking place, and what exists there. [...] Charts such as line charts, column charts, and surface charts, are normally constructed to show the businessman how much and when. Charts have the ability to graphically display the past, present, and anticipated future of an activity. They can be plotted so as to indicate the current direction that is being followed in relationship to what should be followed. They can indicate problems and potential problems, hopefully in time for constructive corrective action to be taken." (Robert D Carlsen & Donald L Vest, "Encyclopedia of Business Charts", 1977)

"Charts and diagrams are the visual presentation of information. Since text and tables of information require close study to obtain the more general impressions of the subject, charts can be used to present readily understandable, easily digestible and, above all, memorable solutions." (Bruce Robertson, "How to Draw Charts & Diagrams", 1988)

"As the size of software systems increases, the algorithms and data structures of the computation no longer constitute the major design problems. When systems are constructed from many components, the organization of the overall system - the software architecture - presents a new set of design problems. This level of design has been addressed in a number of ways including informal diagrams and descriptive terms, module interconnection languages, templates and frameworks for systems that serve the needs of specific domains, and formal models of component integration mechanisms." (David Garlan & Mary Shaw, "An introduction to software architecture", Advances in software engineering and knowledge engineering Vol 1, 1993)

"Delay time, the time between causes and their impacts, can highly influence systems. Yet the concept of delayed effect is often missed in our impatient society, and when it is recognized, it’s almost always underestimated. Such oversight and devaluation can lead to poor decision making as well as poor problem solving, for decisions often have consequences that don’t show up until years later. Fortunately, mind mapping, fishbone diagrams, and creativity/brainstorming tools can be quite useful here." (Stephen G Haines, "The Manager's Pocket Guide to Strategic and Business Planning", 1998)

"Always remember that the model is not the diagram. The diagram’s purpose is to help communicate and explain the model. The code can serve as a repository of the details of the design." (Eric Evans, "Domain-Driven Design: Tackling complexity in the heart of software", 2003)

"Data is transformed into graphics to understand. A map, a diagram are documents to be interrogated. But understanding means integrating all of the data. In order to do this it’s necessary to reduce it to a small number of elementary data. This is the objective of the 'data treatment' be it graphic or mathematic." (Jacques Bertin [interview], 2003)

"Diagrams are a means of communication and explanation, and they facilitate brainstorming. They serve these ends best if they are minimal. Comprehensive diagrams of the entire object model fail to communicate or explain; they overwhelm the reader with detail and they lack meaning." (Eric Evans, "Domain-Driven Design: Tackling complexity in the heart of software", 2003)

"Graphical design notations have been with us for a while [...] their primary value is in communication and understanding. A good diagram can often help communicate ideas about a design, particularly when you want to avoid a lot of details. Diagrams can also help you understand either a software system or a business process. As part of a team trying to figure out something, diagrams both help understanding and communicate that understanding throughout a team. Although they aren't, at least yet, a replacement for textual programming languages, they are a helpful assistant." (Martin Fowler, "UML Distilled: A Brief Guide to the Standard Object Modeling", 2004)

"System Thinking is a common concept for understanding how causal relationships and feedbacks work in an everyday problem. Understanding a cause and an effect enables us to analyse, sort out and explain how changes come about both temporarily and spatially in common problems. This is referred to as mental modelling, i.e. to explicitly map the understanding of the problem and making it transparent and visible for others through Causal Loop Diagrams (CLD)." (Hördur V. Haraldsson, "Introduction to System Thinking and Causal Loop Diagrams", 2004)

"A diagram is a graphic shorthand. Though it is an ideogram, it is not necessarily an abstraction. It is a representation of something in that it is not the thing itself. In this sense, it cannot help but be embodied. It can never be free of value or meaning, even when it attempts to express relationships of formation and their processes. At the same time, a diagram is neither a structure nor an abstraction of structure." (Peter Eisenman, "Written Into the Void: Selected Writings", 1990-2004, 2007)

"Diagrams are information graphics that are made up primarily of geometric shapes, such as rectangles, circles, diamonds, or triangles, that are typically (but not always) interconnected by lines or arrows. One of the major purposes of a diagram is to show how things, people, ideas, activities, etc. interrelate and interconnect. Unlike quantitative charts and graphs, diagrams are used to show interrelationships in a qualitative way." (Robbie T Nakatsu, "Diagrammatic Reasoning in AI", 2010)

"[…] a conceptual model is a diagram connecting variables and constructs based on theory and logic that displays the hypotheses to be tested." (Mary W Celsi et al, "Essentials of Business Research Methods", 2011)

"Geographic maps have the advantage of being true to scale - great for walking. Diagrams have the advantage of being easily imaged and remembered, often true to a non-pedestrian experience, and the ability to open up congestion, reduce empty space, and use real estate efficiently. Hybrids 'mapograms' ? - often have the disadvantages of both map and diagram with none of the corresponding advantages." (Joel Katz, "Designing Information: Human factors and common sense in information design", 2012)

"Diagrams furnish only approximate information. They do not add anything to the meaning of the data and, therefore, are not of much use to a statistician or research worker for further mathematical treatment or statistical analysis. On the other hand, graphs are more obvious, precise and accurate than the diagrams and are quite helpful to the statistician for the study of slopes, rates of change and estimation, (interpolation and extrapolation), wherever possible." (S C Gupta & Indra Gupta, "Business Statistics", 2013) 

"System dynamics [...] uses models and computer simulations to understand behavior of an entire system, and has been applied to the behavior of large and complex national issues. It portrays the relationships in systems as feedback loops, lags, and other descriptors to explain dynamics, that is, how a system behaves over time. Its quantitative methodology relies on what are called 'stock-and-flow diagrams' that reflect how levels of specific elements accumulate over time and the rate at which they change. Qualitative systems thinking constructs evolved from this quantitative discipline." (Karen L Higgins, "Economic Growth and Sustainability: Systems Thinking for a Complex World", 2015)

"To keep accuracy and efficiency of your diagrams appealing to a potential audience, explicitly describe the encoding principles we used. Titles, labels, and legends are the most common ways to define the meaning of the diagram and its elements." (Vasily Pantyukhin, "Principles of Design Diagramming", 2015)

"Upon discovering a visual image, the brain analyzes it in terms of primitive shapes and colors. Next, unity contours and connections are formed. As well, distinct variations are segmented. Finally, the mind attracts active attention to the significant things it found. That process is permanently running to react to similarities and dissimilarities in shapes, positions, rhythms, colors, and behavior. It can reveal patterns and pattern-violations among the hundreds of data values. That natural ability is the most important thing used in diagramming." (Vasily Pantyukhin, "Principles of Design Diagramming", 2015)

"Usually, diagrams contain some noise – information unrelated to the diagram’s primary goal. Noise is decorations, redundant, and irrelevant data, unnecessarily emphasized and ambiguous icons, symbols, lines, grids, or labels. Every unnecessary element draws attention away from the central idea that the designer is trying to share. Noise reduces clarity by hiding useful information in a fog of useless data. You may quickly identify noise elements if you can remove them from the diagram or make them less intense and attractive without compromising the function." (Vasily Pantyukhin, "Principles of Design Diagramming", 2015)

"Models are formal structures represented in mathematics and diagrams that help us to understand the world. Mastery of models improves your ability to reason, explain, design, communicate, act, predict, and explore." (Scott E Page, "The Model Thinker", 2018)

"Some scientists (e.g., econometricians) like to work with mathematical equations; others (e.g., hard-core statisticians) prefer a list of assumptions that ostensibly summarizes the structure of the diagram. Regardless of language, the model should depict, however qualitatively, the process that generates the data - in other words, the cause-effect forces that operate in the environment and shape the data generated." (Judea Pearl & Dana Mackenzie, "The Book of Why: The new science of cause and effect", 2018)

"The calculus of causation consists of two languages: causal diagrams, to express what we know, and a symbolic language, resembling algebra, to express what we want to know. The causal diagrams are simply dot-and-arrow pictures that summarize our existing scientific knowledge. The dots represent quantities of interest, called 'variables', and the arrows represent known or suspected causal relationships between those variables - namely, which variable 'listens' to which others." (Judea Pearl & Dana Mackenzie, "The Book of Why: The new science of cause and effect", 2018)

"The main differences between Bayesian networks and causal diagrams lie in how they are constructed and the uses to which they are put. A Bayesian network is literally nothing more than a compact representation of a huge probability table. The arrows mean only that the probabilities of child nodes are related to the values of parent nodes by a certain formula (the conditional probability tables) and that this relation is sufficient. That is, knowing additional ancestors of the child will not change the formula. Likewise, a missing arrow between any two nodes means that they are independent, once we know the values of their parents. [...] If, however, the same diagram has been constructed as a causal diagram, then both the thinking that goes into the construction and the interpretation of the final diagram change." (Judea Pearl & Dana Mackenzie, "The Book of Why: The new science of cause and effect", 2018)

"Decision trees show the breakdown of the data by one variable then another in a very intuitive way, though they are generally just diagrams that don’t actually encode data visually." (Robert Grant, "Data Visualization: Charts, Maps and Interactive Graphics", 2019)

"The term 'infographics' is used for eye-catching diagrams which get a simple message across. They are very popular in advertising and can convey an impression of scientific, reliable information, but they are not the same thing as data visualization. An infographic will typically only convey a few numbers, and not use visual presentations to allow the reader to make comparisons of their own." (Robert Grant, "Data Visualization: Charts, Maps and Interactive Graphics", 2019)

More quotes on "Diagramming" at the-web-of-knowledge.blogspot.com.  

📉Graphical Representation: Plotting (Just the Quotes)

"Generally speaking, the plotting of a curve consists of graphically representing numbers and equations by the relation of points and lines with reference to other given lines or to a given point." (Allan C Haskell, "How to Make and Use Graphic Charts", 1919)

"It should be a strict rule for all kinds of curve plotting that the horizontal scale must be used. for the independent variable and the vertical scale for the dependent variable. When the curves are plotted by this rule the reader can instantly select a set of conditions from the horizontal scale and read the information from the vertical scale. If there were no rule relating to the arrangement of scales for the independent and dependent variables, the reader would never be able to tell whether he should approach a chart from the vertical scale and read the information from the horizontal scale, or the reverse." (Willard C Brinton, "Graphic Methods for Presenting Facts", 1919)

"The principles of charting and curve plotting are not at all complex, and it is surprising that many business men dodge the simplest charts as though they involved higher mathematics or contained some sort of black magic. [...] The trouble at present is that there are no standards by which graphic presentations can be prepared in accordance with definite rules so that their interpretation by the reader may be both rapid and accurate. It is certain that there will evolve for methods of graphic presentation a few useful and definite rules which will correspond with the rules of grammar for the spoken and written language." (Willard C Brinton, "Graphic Methods for Presenting Facts", 1919) 

"When plotting any curve the vertical scale should, if possible, be chosen so that the zero of the scale will appear on the chart. Otherwise, the reader may assume the bottom of the chart to be zero and so be grossly misled. Zero should always be indicated by a broad line much wider than the ordinary co-ordinate lines used for the background of the chart." (Willard C Brinton, "Graphic Methods for Presenting Facts", 1919)

"If a chart contains a number of series which vary widely in individual magnitude, optical distortion may result from the necessarily sharp changes in the angle of the curves. The space between steeply rising or falling curves always appears narrower than the vertical distance between the plotting points." (Rufus R Lutz, "Graphic Presentation Simplified", 1949)

"In line charts the grid structure plays a controlling role in interpreting facts. The number of vertical rulings should be sufficient to indicate the frequency of the plottings, facilitate the reading of the time values on the horizontal scale. and indicate the interval or subdivision of time." (Anna C Rogers, "Graphic Charts Handbook", 1961)

"Simplicity, accuracy, appropriate size, proper proportion, correct emphasis, and skilled execution - these are the factors that produce the effective chart. To achieve simplicity your chart must be designed with a definite audience in mind, show only essential information. Technical terms should be absent as far as possible. And in case of doubt it is wiser to oversimplify than to make matters unduly complex. Be careful to avoid distortion or misrepresentation. Accuracy in graphics is more a matter of portraying a clear reliable picture than reiterating exact values. Selecting the right scales and employing authoritative titles and legends are as important as precision plotting. The right size of a chart depends on its probable use, its importance, and the amount of detail involved." (Anna C Rogers, "Graphic Charts Handbook", 1961)

"Learning to make graphs involves two things: (l) the techniques of plotting statistics, which might be called the artist's job; and (2) understanding the statistics. When you know how to work out graphs, all kinds of statistics will probably become more interesting to you." (Dyno Lowenstein, "Graphs", 1976)

"For most line charts the maximum number of plotted lines should not exceed five; three or fewer is the ideal number. When multiple plotted lines are shown each line should be differentiated by using" (a) a different type of line and/or" (b) different plotting marks, if shown, and" (c) clearly differentiated labeling." (Robert Lefferts, "Elements of Graphics: How to prepare charts and graphs for effective reports", 1981)

"Frequently we can increase the informativeness of a graph by removing structure from the data once we have identified it, so that subsequent plots are free of its dominating influence and can help us see finer structure or subtler effects. This usually means (l) partitioning the data, or (2) plotting differences or ratios, or" (3) fitting a model and taking the residuals as a new set of data for further study." (John M Chambers et al, "Graphical Methods for Data Analysis", 1983)

"Generally speaking, a good display is one in which the visual impact of its components is matched to their importance in the context of the analysis. Consider the issue of overplotting." (John M Chambers et al, "Graphical Methods for Data Analysis", 1983)

"Plotting on power-transformed scales (either cube roots or logs) is recommended only in those cases where the distribution is very asymmetric and the reference configuration for the untransformed plot would be a straight line through the origin." (John M Chambers et al, "Graphical Methods for Data Analysis", 1983)

"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)

"Plotting data is a useful first stage to any analysis and will show extreme observations together with any discernible patterns. In addition the relative sizes of categories are easier to see in a diagram" (bar chart or pie chart) than in a table. Graphs are useful as they can be assimilated quickly, and are particularly helpful when presenting information to an audience. Tables can be useful for displaying information about many variables at once, while graphs can be useful for showing multiple observations on groups or individuals. Although there are no hard and fast rules about when to use a graph and when to use a table, in the context of a report or a paper it is often best to use tables so that the reader can scrutinise the numbers directly." (Jenny Freeman et al, "How to Display Data", 2008)

"With time series though, there is absolutely no substitute for plotting. The pertinent pattern might end up being a sharp spike followed by a gentle taper down. Or, maybe there are weird plateaus. There could be noisy spikes that have to be filtered out. A good way to look at it is this: means and standard deviations are based on the naïve assumption that data follows pretty bell curves, but there is no corresponding 'default' assumption for time series data" (at least, not one that works well with any frequency), so you always have to look at the data to get a sense of what’s normal. [...] Along the lines of figuring out what patterns to expect, when you are exploring time series data, it is immensely useful to be able to zoom in and out." (Field Cady, "The Data Science Handbook", 2017)

"Plotting numbers on a chart does not make you a data analyst. Knowing and understanding your data before you communicate it to your audience does."  (Andy Kriebel & Eva Murray, "#MakeoverMonday: Improving How We Visualize and Analyze Data, One Chart at a Time", 2018)

Visually plotting time series data against a point in time reveals patterns relative to that period, thus allowing the reader to understand growth and decline before and after the given point in time." (Andy Kriebel & Eva Murray, "#MakeoverMonday: Improving How We Visualize and Analyze Data, One Chart at a Time", 2018)

📉Graphical Representation: Area (Just the Quotes)

"In general, the comparison of two circles of different size should be strictly avoided. Many excellent works on statistics approve the comparison of circles of different size, and state that the circles should always be drawn to represent the facts on an area basis rather than on a diameter basis. The rule, however, is not always followed and the reader has no way of telling whether the circles compared have been drawn on a diameter basis or on an area basis, unless the actual figures for the data are given so that the dimensions may be verified." (Willard C Brinton, "Graphic Methods for Presenting Facts", 1919)

"Readers of statistical diagrams should not be required to compare magnitudes in more than one dimension. Visual comparisons of areas are particularly inaccurate and should not be necessary in reading any statistical graphical diagram." (William C Marshall, "Graphical methods for schools, colleges, statisticians, engineers and executives", 1921)

"A chart without a border line has several advantages. It is not limited to a designated area. The irregular white space surrounding it makes it more adaptable to any page size. It may be more readily placed either horizontally or vertically on the page, so long as the reduction in the size of the chart does not destroy legibility of lettering." (Mary E Spear, "Charting Statistics", 1952)

"The pie or sector chart makes a comparison of various components with each other and with the whole. However, this type should be used sparingly, especially when there are many segments. It is not only difficult to compare area segments, but most difficult to label them properly. When there are many divisions of the data, a bar chart would give greater clarity." (Mary E Spear, "Charting Statistics", 1952)

"Charts and graphs represent an extremely useful and flexible medium for explaining, interpreting, and analyzing numerical facts largely by means of points, lines, areas, and other geometric forms and symbols. They make possible the presentation of quantitative data in a simple, clear, and effective manner and facilitate comparison of values, trends, and relationships. Moreover, charts and graphs possess certain qualities and values lacking in textual and tabular forms of presentation." (Calvin F Schmid, "Handbook of Graphic Presentation", 1954)

"Circles of different size, however cannot properly be used to compare the size of different totals. This is because the reader does not know whether to compare the diameters or the areas (which vary as the squares of the diameters), and is likely to misjudge the comparison in either ease. Usually the circles are drawn so that their diameters are in correct proportion to each other; but then the area comparison is exaggerated. Component bars should be used to show totals of different size since their one dimension lengths can be easily judged not only for the totals themselves but for the component parts as well. Circles, therefore, can show proportions properly by variations in angles of sectors but not by variations in diameters."  (Anna C Rogers, "Graphic Charts Handbook", 1961)

"The histogram, with its columns of area proportional to number, like the bar graph, is one of the most classical of statistical graphs. Its combination with a fitted bell-shaped curve has been common since the days when the Gaussian curve entered statistics. Yet as a graphical technique it really performs quite poorly. Who is there among us who can look at a histogram-fitted Gaussian combination and tell us, reliably, whether the fit is excellent, neutral, or poor? Who can tell us, when the fit is poor, of what the poorness consists? Yet these are just the sort of questions that a good graphical technique should answer at least approximately." (John W Tukey, "The Future of Processes of Data Analysis", 1965)

"The varieties of circle charts are necessarily limited by the lack of basic design variation - a circle is a circle! Also, a circle can be considered as representing only one unit of area. regardless of its size. Thus, circle charts have limited applications, i.e., to show how a given quantity (area) is divided among its component parts,' or to show changes in the variable by showing area changes. A circle chart almost always presents some form of a part-to-total relationship." (Cecil H Meyers, "Handbook of Basic Graphs: A modern approach", 1970)

"The space between columns, on the other hand, should be just sufficient to separate them clearly, but no more. The columns should not, under any circumstances, be spread out merely to fill the width of the type area. […] Sometimes, however, it is difficult to avoid undesirably large gaps between columns, particularly where the data within any given column vary considerably in length. This problem can sometimes be solved by reversing the order of the columns […]. In other instances the insertion of additional space after every fifth entry or row can be helpful, […] but care must be taken not to imply that the grouping has any special meaning." (Linda Reynolds & Doig Simmonds, "Presentation of Data in Science" 4th Ed, 1984)

"Scatter charts show the relationships between information, plotted as points on a grid. These groupings can portray general features of the source data, and are useful for showing where correlationships occur frequently. Some scatter charts connect points of equal value to produce areas within the grid which consist of similar features." (Bruce Robertson, "How to Draw Charts & Diagrams", 1988)

"There is a technical difference between a bar chart and a histogram in that the number represented is proportional to the length of bar in the former and the area in the latter. This matters if non-uniform binning is used. Bar charts can be used for qualitative or quantitative data, whereas histograms can only be used for quantitative data, as no meaning can be attached to the width of the bins if the data are qualitative." (Roger J Barlow, "Statistics: A guide to the use of statistical methods in the physical sciences", 1989)

"Using area to encode quantitative information is a poor graphical method. Effects that can be readily perceived in other visualizations are often lost in an encoding by area." (William S Cleveland, "Visualizing Data", 1993)

"Area graphs are generally not used to convey specific values. Instead, they are most frequently used to show trends and relationships, to identify and/or add emphasis to specific information by virtue of the boldness of the shading or color, or to show parts-of-the-whole." (Robert L Harris, "Information Graphics: A Comprehensive Illustrated Reference", 1996) 

"Although in most cases the actual value designated by a bar is determined by the location of the end of the bar, many people associate the length or area of the bar with its value. As long as the scale is linear, starts at zero, is continuous, and the bars are the same width, this presents no problem. When any of these conditions are changed, the potential exists that the graph will be misinterpreted." (Robert L Harris, "Information Graphics: A Comprehensive Illustrated Reference", 1996)

"Grouped area graphs sometimes cause confusion because the viewer cannot determine whether the areas for the data series extend down to the zero axis. […] Grouped area graphs can handle negative values somewhat better than stacked area graphs but they still have the problem of all or portions of data curves being hidden by the data series towards the front." (Robert L Harris, "Information Graphics: A Comprehensive Illustrated Reference", 1996)

"A Venn diagram is a simple representation of the sample space, that is often helpful in seeing 'what is going on'. Usually the sample space is represented by a rectangle, with individual regions within the rectangle representing events. It is often helpful to imagine that the actual areas of the various regions in a Venn diagram are in proportion to the corresponding probabilities. However, there is no need to spend a long time drawing these diagrams - their use is simply as a reminder of what is happening." (Graham Upton & Ian Cook, "Introducing Statistics", 2001)

"This pie chart violates several of the rules suggested by the question posed in the introduction. First, immediacy: the reader has to turn to the legend to find out what the areas represent; and the lack of color makes it very difficult to determine which area belongs to what code. Second, the underlying structure of the data is completely ignored. Third, a tremendous amount of ink is used to display eight simple numbers." (Gerald van Belle, "Statistical Rules of Thumb", 2002)

"Choose scales wisely, as they have a profound influence on the interpretation of graphs. Not all scales require that zero be included, but bar graphs and other graphs where area is judged do require it." (Naomi B Robbins, "Creating More effective Graphs", 2005)

"Areas surrounding data-lines may generate unintentional optical clutter. Strong frames produce melodramatic but content-diminishing visual effects. [...] A good way to assess a display for unintentional optical clutter is to ask 'Do the prominent visual effects convey relevant content?'" (Edward R Tufte, "Beautiful Evidence", 2006)

"Histograms use area to represent counts of a distribution. This makes them somewhat related to barcharts and mosaic plots, although the number or the width of the bins of a histogram is not determined a priori and the bins are drawn without gaps between them reflecting the continuous scale of the data. Whereas barcharts and mosaic plots show the exact distribution of the sample, a histogram is always just one approximation to the distribution of the data. Sometimes histograms are also used as crude density estimators for some 'true', but usually unknown, underlying distribution for the data. There are much better density estimation methods that produce smooth distribution displays." (Antony Unwin et al [in "Graphics of Large Datasets: Visualizing a Million"], 2006)

"The notion of outcomes covering a space is a very useful mental image, as it ties in strongly with the use of Venn diagrams and tables for clarifying the nature of possible events resulting from a trial. There are two important aspects to this. First, when enumerating the various outcomes that comprise an event, the number of (equally. likely) outcomes should correspond, visually, with the area of that part of the diagram represented by the event in question - the greater the probability, the larger the area. Secondly, where events overlap (for example, when rolling a die, consider the two events 'getting an even score' and 'getting a score greater than 2' ), the various regions in the Venn diagram help to clarify the various combinations of events that might occur." (Alan Graham, "Developing Thinking in Statistics", 2006)

"It is important to pay heed to the following detail: a disadvantage of logarithmic diagrams is that a graphical integration is not possible, i.e., the area under the curve (the integral) is of no relevance." (Manfred Drosg, "Dealing with Uncertainties: A Guide to Error Analysis", 2007)

"The data [in tables] should not be so spaced out that it is difficult to follow or so cramped that it looks trapped. Keep columns close together; do not spread them out more than is necessary. If the columns must be spread out to fit a particular area, such as the width of a page, use a graphic device such as a line or screen to guide the reader’s eye across the row." (Dennis K Lieu & Sheryl Sorby, "Visualization, Modeling, and Graphics for Engineering Design", 2009)

"A unimodal histogram that is not symmetric is said to be skewed. If the upper tail of the histogram stretches out much farther than the lower tail, then the distribution of values is positively skewed or right skewed. If, on the other hand, the lower tail is much longer than the upper tail, the histogram is negatively skewed or left skewed." (Roxy Peck et al, "Introduction to Statistics and Data Analysis" 4th Ed., 2012)

"The use of the density scale to construct the histogram ensures that the area of each rectangle in the histogram will be proportional to the corresponding relative frequency. The formula for density can also be used when class widths are equal. However, when the intervals are of equal width, the extra arithmetic required to obtain the densities is unnecessary." (Roxy Peck et al, "Introduction to Statistics and Data Analysis" 4th Ed., 2012)

"Area can also make data seem more tangible or relatable, because physical objects take up space. A circle or a square uses more space than a dot on a screen or paper. There’s less abstraction between visual cue and real world." (Nathan Yau, "Data Points: Visualization That Means Something", 2013)

"One very common problem in data visualization is that encoding numerical variables to area is incredibly popular, but readers can’t translate it back very well." (Robert Grant, "Data Visualization: Charts, Maps and Interactive Graphics", 2019)

📉Graphical Representation: Histograms (Just the Quotes)

"The histogram, with its columns of area proportional to number, like the bar graph, is one of the most classical of statistical graphs. Its combination with a fitted bell-shaped curve has been common since the days when the Gaussian curve entered statistics. Yet as a graphical technique it really performs quite poorly. Who is there among us who can look at a histogram-fitted Gaussian combination and tell us, reliably, whether the fit is excellent, neutral, or poor? Who can tell us, when the fit is poor, of what the poorness consists? Yet these are just the sort of questions that a good graphical technique should answer at least approximately." (John W Tukey, "The Future of Processes of Data Analysis", 1965)

"There is a technical difference between a bar chart and a histogram in that the number represented is proportional to the length of bar in the former and the area in the latter. This matters if non-uniform binning is used. Bar charts can be used for qualitative or quantitative data, whereas histograms can only be used for quantitative data, as no meaning can be attached to the width of the bins if the data are qualitative." (Roger J Barlow, "Statistics: A guide to the use of statistical methods in the physical sciences", 1989)

"90 percent of all problems can be solved by using the techniques of data stratification, histograms, and control charts. Among the causes of nonconformance, only one-fifth or less are attributable to the workers." (Kaoru Ishikawa, The Quality Management Journal Vol. 1, 1993)

"Averages, ranges, and histograms all obscure the time-order for the data. If the time-order for the data shows some sort of definite pattern, then the obscuring of this pattern by the use of averages, ranges, or histograms can mislead the user. Since all data occur in time, virtually all data will have a time-order. In some cases this time-order is the essential context which must be preserved in the presentation." (Donald J Wheeler," Understanding Variation: The Key to Managing Chaos" 2nd Ed., 2000)

"The ordinary histogram is constructed by binning data on a uniform grid. Although this is probably the most widely used statistical graphic, it is one of the more difficult ones to compute. Several problems arise, including choosing the number of bins (bars) and deciding where to place the cutpoints between bars." (Leland Wilkinson, "The Grammar of Graphics" 2nd Ed., 2005)

"The plot tells us the data are granular in the data source, something we could not ascertain with the histogram. There is an important lesson here. Statistics texts and statistical packages that recommend the histogram as the graphical starting point for a data analysis are giving bad advice. The same goes for kernel density estimates. These are appropriate second stages for graphical data analysis. The best starting point for getting a sense of the distribution of a variable is a tally, stem-and-leaf, or a dot plot. A dot plot is a special case of a tally (perhaps best thought of as a delta-neighborhood tally). Once we see that the data are not granular, we may move on to a histogram or kernel density, which smooths the data more than a dot plot." (Leland Wilkinson, "The Grammar of Graphics" 2nd Ed., 2005)

"Histograms use area to represent counts of a distribution. This makes them somewhat related to barcharts and mosaic plots, although the number or the width of the bins of a histogram is not determined a priori and the bins are drawn without gaps between them reflecting the continuous scale of the data. Whereas barcharts and mosaic plots show the exact distribution of the sample, a histogram is always just one approximation to the distribution of the data. Sometimes histograms are also used as crude density estimators for some 'true', but usually unknown, underlying distribution for the data. There are much better density estimation methods that produce smooth distribution displays." (Antony Unwin et al [in "Graphics of Large Datasets: Visualizing a Million"], 2006)

"How would a million be visualized today? If you have ever drawn a histogram or a scatterplot of a million cases, you know that it is possible, but that there are problems. The screen resolution of a computer cannot be high enough to show very small bars in the histogram, and in regions of high density the scatterplots look like black blobs with huge numbers of points piled on top of one another. (It is noteworthy - and useful - that the weaknesses of the two kinds of plot arise at opposite extremes of the distributional densities.) So what should be visualized? If the distributional form of the bulk of the data is of interest, then the histogram will be fine for one-dimensional views (and it may give some information about outliers too). If individual outliers are of interest, then the scatterplot will be pretty good (and it will give a fair bit of distributional information as well). One aim might be described as global, attempting to summarise the main structure, and the other as local, attempting to identify individual features. Ideally, both kinds of plot are needed to satisfy both aims." (Antony Unwin et al [in "Graphics of Large Datasets: Visualizing a Million"], 2006)

"Use of a histogram should be strictly reserved for continuous numerical data or for data that can be effectively modelled as continuous […]. Unlike bar charts, therefore, the bars of a histogram corresponding to adjacent intervals should not have gaps between them, for obvious reasons." (Alan Graham, "Developing Thinking in Statistics", 2006)

"A histogram consists of the outline of bars of equal width and appropriate length next to each other. By connecting the frequency values at the position of the nominal values (the midpoints of the intervals) with straight lines, a frequency polygon is obtained. Attaching classes with frequency zero at either end makes the area (the integral) under the frequency polygon equal  to that under the histogram." (Manfred Drosg, "Dealing with Uncertainties: A Guide to Error Analysis", 2007)

"Before calculating a confidence interval for a mean, first check that one of the situations just described holds. To determine whether the data are bell-shaped or skewed, and to check for outliers, plot the data using a histogram, dotplot, or stemplot. A boxplot can reveal outliers and will sometimes reveal skewness, but it cannot be used to determine the shape otherwise. The sample mean and median can also be compared to each other. Differences between the mean and the median usually occur if the data are skewed - that is, are much more spread out in one direction than in the other." (Jessica M Utts & Robert F Heckard, "Mind on Statistics", 2007)

"Histograms are powerful in cases where meaningful class breaks can be defined and classes are used to select intervals and groups in the data. However, they often perform poorly when it comes to the visualization of a distribution." (Martin Theus & Simon Urbanek, "Interactive Graphics for Data Analysis: Principles and Examples", 2009) 

"Need to consider outliers as they can affect statistics such as means, standard deviations, and correlations. They can either be explained, deleted, or accommodated (using either robust statistics or obtaining additional data to fill-in). Can be detected by methods such as box plots, scatterplots, histograms or frequency distributions." (Randall E Schumacker & Richard G Lomax, "A Beginner’s Guide to Structural Equation Modeling" 3rd Ed., 2010)

"A histogram for discrete numerical data is a graph of the frequency or relative frequency distribution, and it is similar to the bar chart for categorical data. Each frequency or relative frequency is represented by a rectangle centered over the corresponding value (or range of values) and the area of the rectangle is proportional to the corresponding frequency or relative frequency." (Roxy Peck et al, "Introduction to Statistics and Data Analysis" 4th Ed., 2012)

"A unimodal histogram that is not symmetric is said to be skewed. If the upper tail of the histogram stretches out much farther than the lower tail, then the distribution of values is positively skewed or right skewed. If, on the other hand, the lower tail is much longer than the upper tail, the histogram is negatively skewed or left skewed." (Roxy Peck et al, "Introduction to Statistics and Data Analysis" 4th Ed., 2012)

"Histograms are often mistaken for bar charts but there are important differences. Histograms show distribution through the frequency of quantitative values (y axis) against defined intervals of quantitative values(x axis). By contrast, bar charts facilitate comparison of categorical values. One of the distinguishing features of a histogram is the lack of gaps between the bars [...]" (Andy Kirk, "Data Visualization: A successful design process", 2012)

"The use of the density scale to construct the histogram ensures that the area of each rectangle in the histogram will be proportional to the corresponding relative frequency. The formula for density can also be used when class widths are equal. However, when the intervals are of equal width, the extra arithmetic required to obtain the densities is unnecessary." (Roxy Peck et al, "Introduction to Statistics and Data Analysis" 4th Ed., 2012)

"Histograms and frequency polygons display a schematic of a numeric variable's frequency distribution. These plots can show us the center and spread of a distribution, can be used to judge the skewness, kurtosis, and modicity of a distribution, can be used to search for outliers, and can help us make decisions about the symmetry and normality of a distribution." (Forrest W Young et al, "Visual Statistics: Seeing data with dynamic interactive graphics", 2016)

"A histogram represents the frequency distribution of the data. Histograms are similar to bar charts but group numbers into ranges. Also, a histogram lets you show the frequency distribution of continuous data. This helps in analyzing the distribution (for example, normal or Gaussian), any outliers present in the data, and skewness." (Umesh R Hodeghatta & Umesha Nayak, "Business Analytics Using R: A Practical Approach", 2017)

📉Graphical Representation: Charts (Just the Quotes)

"To a very striking degree our culture has become a Statistical culture. Even a person who may never have heard of an index number is affected [...] by [...] of those index numbers which describe the cost of living. It is impossible to understand Psychology, Sociology, Economics, Finance or a Physical Science without some general idea of the meaning of an average, of variation, of concomitance, of sampling, of how to interpret charts and tables." (Carrol D Wright, 1887)

"Graphic representation by means of charts depends upon the super-position of special lines or curves upon base lines drawn or ruled in a standard manner. For the economic construction of these charts as well as their correct use it is necessary that the standard rulings be correctly designed." (Allan C Haskell, "How to Make and Use Graphic Charts", 1919)

"It is not possible to lay down any hard and fast rules for determining what chart is the best for any given problem. Ordinarily that one is the best which will produce the quickest and clearest results. but unfortunately it is not always possible to construct the clearest one in the least time. Experience is the best guide. Generally speaking, a rectilinear chart is best adapted for equations of the first degree, logarithmic for those other than the first degree and not containing over two variables, and alignment charts where there are three or more variables. However, nearly every person becomes more or less familiar with one type of chart and prefers to adhere to the use of that type because he does not care to take the time and trouble to find out how to use the others. It is best to know what the possibilities of all types are and to be governed accordingly when selecting one or the other for presenting or working out certain data." (Allan C Haskell, "How to Make and Use Graphic Charts", 1919)

"Many people imagine that graphic charts cannot be understood except by expert mathematicians who have devoted years of study to the subject. This is a mistaken idea, and if instead of passing over charts as if they were something beyond their comprehension more people would make an effort to read them, much valuable time would be saved. It is true that some charts covering technical data are difficult even for an expert mathematician to understand, but this is more often the fault of the person preparing the charts than of the system." (Allan C Haskell, "How to Make and Use Graphic Charts", 1919)

"The best-known function of charts is for demonstration purposes, to show up facts. When so presented they do not require a trained mind for their appreciation, since the spatial sense through the optic nerve is among the commonest of the human attributes." (Allan C Haskell, "How to Make and Use Graphic Charts", 1919)

"Factual science may collect statistics, and make charts. But its predictions are, as has been well said, but past history reversed." (John Dewey, "Art as Experience", 1934)

"Although, the tabular arrangement is the fundamental form for presenting a statistical series, a graphic representation - in a chart or diagram - is often of great aid in the study and reporting of statistical facts. Moreover, sometimes statistical data must be taken, in their sources, from graphic rather than tabular records." (William L Crum et al, "Introduction to Economic Statistics", 1938)

"Graphic charts have often been thought to be tools of those alone who are highly skilled in mathematics, but one needs to have a knowledge of only eighth-grade arithmetic to use intelligently even the logarithmic or ratio chart, which is considered so difficult by those unfamiliar with it. […] If graphic methods are to be most effective, those who are unfamiliar with charts must give some attention to their fundamental structure. Even simple charts may be misinterpreted unless they are thoroughly understood. For instance, one is not likely to read an arithmetic chart correctly unless he also appreciates the significance of a logarithmic chart." (John R Riggleman & Ira N Frisbee, "Business Statistics", 1938)

"One of the greatest values of the graphic chart is its use in the analysis of a problem. Ordinarily, the chart brings up many questions which require careful consideration and further research before a satisfactory conclusion can be reached. A properly drawn chart gives a cross-section picture of the situation. While charts may bring out. hidden facts in tables or masses of data, they cannot take the place of careful, analysis. In fact, charts may be dangerous devices when in the hands of those unwilling to base their interpretations upon careful study. This, however, does not detract from their value when they are properly used as aids in solving statistical problems." (John R Riggleman & Ira N Frisbee, "Business Statistics", 1938)

"The eye can accurately appraise only very few features of a diagram, and consequently a complicated or confusing diagram will lead the reader astray. The fundamental rule for all charting is to use a plan which is simple and which takes account, in its arrangement of the facts to be presented, of the above-mentioned capacities of the eye."  (William L Crum et al, "Introduction to Economic Statistics", 1938)

"In making up the charts, keep them simple. One idea to a page and not too much detail is a good rule. Try to get variety in the subject matter - now a chart, next a diagram, then a tabulation. Such variety helps hold audience attention." (Edward J Hegarty, "How to Use a Set of Display Charts", The American Statistician Vol. 2 (5), 1948)

"If the audience can see all the charts at once, they may get a different story from the one you want them to get. Show the charts one at a time. If you have only one chart, keep it covered until you are ready to use it. Take full advantage of the element of surprise. If you use charts which open like a book, use only one page for the message." (Edward J Hegarty, "How to Use a Set of Display Charts", The American Statistician Vol. 2 (5), 1948)

"Try telling the story in words different from those on the charts. […] If the chart shows a picture, describe the picture. Tell what it shows and why it is shown. If it is a diagram, explain it. Don't leave the audience to figure it out. No matter how simple the story shown, tell it in your own words: but remember that explaining a chart doesn't mean reading it out loud." (Edward J Hegarty, "How to Use a Set of Display Charts", The American Statistician Vol. 2 (5), 1948)

"Extrapolations are useful, particularly in the form of soothsaying called forecasting trends. But in looking at the figures or the charts made from them, it is necessary to remember one thing constantly: The trend to now may be a fact, but the future trend represents no more than an educated guess. Implicit in it is 'everything else being equal' and 'present trends continuing'. And somehow everything else refuses to remain equal." (Darell Huff, "How to Lie with Statistics", 1954)

"Planning is essentially the analysis and measurement of materials and processes in advance of the event and the perfection of records so that we may know exactly where we are at any given moment. In short it is attempting to steer each operation and department by chart and compass and chronometer - not by guess and by God." (Lyndall Urwick, "The Pattern of Management", 1956)

"However informative and well designed a statistical table may be, as a medium for conveying to the reader an immediate and clear impression of its content, it is inferior to a good chart or graph. Many people are incapable of comprehending large masses of information presented in tabular form; the figures merely confuse them. Furthermore, many such people are unwilling to make the effort to grasp the meaning of such data. Graphs and charts come into their own as a means of conveying information in easily comprehensible form." (Alfred R Ilersic, "Statistics", 1959)

"Simplicity, accuracy. appropriate size, proper proportion, correct emphasis, and skilled execution - these are the factors that produce the effective chart. To achieve simplicity your chart must be designed with a definite audience in mind, show only essential information. Technical terms should be absent as far as possible. And in case of doubt it is wiser to oversimplify than to make matters unduly complex. Be careful to avoid distortion or misrepresentation. Accuracy in graphics is more a matter of portraying a clear reliable picture than reiterating exact values. Selecting the right scales and employing authoritative titles and legends are as important as precision plotting. The right size of a chart depends on its probable use, its importance, and the amount of detail involved." (Anna C Rogers, "Graphic Charts Handbook", 1961)

"Without adequate planning. it is seldom possible to achieve either proper emphasis of each component element within the chart or a presentation that is pleasing in its entirely. Too often charts are developed around a single detail without sufficient regard for the work as a whole. Good chart design requires consideration of these four major factors: (1) size, (2) proportion, (3) position and margins, and (4) composition." (Anna C Rogers, "Graphic Charts Handbook", 1961)

"A model is a qualitative or quantitative representation of a process or endeavor that shows the effects of those factors which are significant for the purposes being considered. A model may be pictorial, descriptive, qualitative, or generally approximate in nature; or it may be mathematical and quantitative in nature and reasonably precise. It is important that effective means for modeling be understood such as analog, stochastic, procedural, scheduling, flow chart, schematic, and block diagrams." (Harold Chestnut, "Systems Engineering Tools", 1965)

"Charts not only tell what was, they tell what is; and a trend from was to is (projected linearly into the will be) contains better percentages than clumsy guessing." (Robert A Levy, "The Relative Strength Concept of Common Stock Forecasting", 1968)

"Charts and graphs are a method of organizing information for a unique purpose. The purpose may be to inform, to persuade, to obtain a clear understanding of certain facts, or to focus information and attention on a particular problem. The information contained in charts and graphs must, obviously, be relevant to the purpose. For decision-making purposes. information must be focused clearly on the issue or issues requiring attention. The need is not simply for 'information', but for structured information, clearly presented and narrowed to fit a distinctive decision-making context. An advantage of having a 'formula' or 'model' appropriate to a given situation is that the formula indicates what kind of information is needed to obtain a solution or answer to a specific problem." (Cecil H Meyers, "Handbook of Basic Graphs: A modern approach", 1970)

"It is almost impossible to define 'time-sequence chart' in a clear and unambiguous manner because of the many forms and adaptations open to this type of chart. However. it might be said that, in essence, time-sequence chart portrays a chain of activities through time, indicates the type of activity in each link of the chain, shows clearly the position of the link in the total sequence chain, and indicates the duration of each activity. The time sequence chart may also contain verbal elements explaining when to begin an activity, how long to continue the activity, and a description of the activity. The chart may also indicate when to blend a given activity with another and the point at which a given activity is completed. The basic time-sequence chart may also be accompanied by verbal explanations and by secondary or contributory charts." (Cecil H Meyers, "Handbook of Basic Graphs: A modern approach", 1970)

"Pencil and paper for construction of distributions, scatter diagrams, and run-charts to compare small groups and to detect trends are more efficient methods of estimation than statistical inference that depends on variances and standard errors, as the simple techniques preserve the information in the original data." (W Edwards Deming, "On Probability as Basis for Action", American Statistician Vol. 29 (4), 1975)

"The types of graphics used in operating a business fall into three main categories: diagrams, maps, and charts. Diagrams, such as organization diagrams, flow diagrams, and networks, are usually intended to graphically portray how an activity should be, or is being, accomplished, and who is responsible for that accomplishment. Maps such as route maps, location maps, and density maps, illustrate where an activity is, or should be, taking place, and what exists there. [...] Charts such as line charts, column charts, and surface charts, are normally constructed to show the businessman how much and when. Charts have the ability to graphically display the past, present, and anticipated future of an activity. They can be plotted so as to indicate the current direction that is being followed in relationship to what should be followed. They can indicate problems and potential problems, hopefully in time for constructive corrective action to be taken." (Robert D Carlsen & Donald L Vest, "Encyclopedia of Business Charts", 1977)

"What you may call a graph, someone else may call a chart, for both terms are used for the same thing. Actually, however. the word 'chart' was originally used only for navigation maps and diagrams. Most people agree that it is best to leave the term 'chart' to the navigators." (Dyno Lowenstein, "Graphs", 1976)

"A good graphic must give the impression that its various parts all belong together. They must be arranged in such a way that the illustration looks like a single entity. A good graphic chart should be more than just the sum of its individual lines, shapes, and shades. It should be more than the individual bars in a bar chart, more than the pieces of a pie chart, more than the boxes in a flow chart. Unity requires the establishment of coherent relationships among the component parts of the drawing. These relationships can be depicted in a very direct manner through the use of connecting lines that serve to connect shapes." (Robert Lefferts, "Elements of Graphics: How to prepare charts and graphs for effective reports", 1981)

"Graphic charts are ways of presenting quantitative as well as qualitative information in an efficient and effective visual form. Numbers and ideas presented graphically are often more easily understood. remembered. and integrated than when they are presented in narrative or tabular form. Descriptions. trends. relationships, and comparisons can be made more apparent. Less time is required to present and comprehend information when graphic methods are employed. As the old truism states, 'One picture is worth a thousand words.'" (Robert Lefferts, "Elements of Graphics: How to prepare charts and graphs for effective reports", 1981)

"Graphic forms help us to perform and influence two critical functions of the mind: the gathering of information and the processing of that information. Graphs and charts are ways to increase the effectiveness and the efficiency of transmitting information in a way that enhances the reader's ability to process that information. Graphics are tools to help give meaning to information because they go beyond the provision of information and show relationships, trends, and comparisons. They help to distinguish which numbers and which ideas are more important than others in a presentation." (Robert Lefferts, "Elements of Graphics: How to prepare charts and graphs for effective reports", 1981)

"Unlike some art forms. good graphics should be as concrete. geometrical, and representational as possible. A rectangle should be drawn as a rectangle, leaving nothing to the reader's imagination about what you are trying to portray. The various lines and shapes used in a graphic chart should be arranged so that it appears to be balanced. This balance is a result of the placement of shapes and lines in an orderly fashion." (Robert Lefferts, "Elements of Graphics: How to prepare charts and graphs for effective reports", 1981)

"We would wish ‘numerate’ to imply the possession of two attributes. The first of these is an ‘at-homeness’ with numbers and an ability to make use of mathematical skills which enable an individual to cope with the practical mathematical demands of his everyday life. The second is ability to have some appreciation and understanding of information which is presented in mathematical terms, for instance in graphs, charts or tables or by reference to percentage increase or decrease." (Cockcroft Committee, "Mathematics Counts: A Report into the Teaching of Mathematics in Schools", 1982)

"[…] the only worse design than a pie chart is several of them, for then the viewer is asked to compare quantities located in spatial disarray both within and between pies. […] Given their low data-density and failure to order numbers along a visual dimension, pie charts should never be used." (Edward R Tufte, "The Visual Display of Quantitative Information", 1983)

"[decision trees are the] most picturesque of all the allegedly scientific aids to making decisions. The analyst charts all the possible outcomes of different options, and charts all the latters' outcomes, too. This produces a series of stems and branches (hence the tree). Each of the chains of events is given a probability and a monetary value." (Robert Heller, "The Pocket Manager", 1987)

"A chart is a bridge between you and your readers. It reveals your skills at comprehending the source information, at mastering presentation methods and at producing the design. Its success depends a great deal on your readers ' understanding of what you are saying, and how you are saying it. Consider how they will use your chart. Will they want to find out from it more information about the subject? Will they just want a quick impression of the data? Or will they use it as a source for their own analysis? Charts rely upon a visual language which both you and your readers must understand." (Bruce Robertson, "How to Draw Charts & Diagrams", 1988)

"Charts and diagrams are the visual presentation of information. Since text and tables of information require close study to obtain the more general impressions of the subject, charts can be used to present readily understandable, easily digestible and, above all, memorable solutions." (Bruce Robertson, "How to Draw Charts & Diagrams", 1988)

"Charts offer opportunities to distort information, to misinform. An old adage can be extended to read: 'There are lies, damned lies, statistics and charts'. Our visual impressions are often more memorable than our understanding of the facts they describe. [...] Never let your design enthusiasms overrule your judgement of the truth." (Bruce Robertson, "How to Draw Charts & Diagrams", 1988)

"Wherever information has to be presented, charts offer an alternative to text and tables of figures. They are concise, memorable often intelligible without language, and can make significant additions to the story." (Bruce Robertson, "How to Draw Charts & Diagrams", 1988)

"90 percent of all problems can be solved by using the techniques of data stratification, histograms, and control charts. Among the causes of nonconformance, only one-fifth or less are attributable to the workers." (Kaoru Ishikawa, The Quality Management Journal Vol. 1, 1993)

"A good chart delineates and organizes information. It communicates complex ideas, procedures, and lists of facts by simplifying, grouping, and setting and marking priorities. By spatial organization, it should lead the eye through information smoothly and efficiently." (Mary H Briscoe, "Preparing Scientific Illustrations: A guide to better posters, presentations, and publications" 2nd ed., 1995)

"Pie charts have severe perceptual problems. Experiments in graphical perception have shown that compared with dot charts, they convey information far less reliably. But if you want to display some data, and perceiving the information is not so important, then a pie chart is fine." (Richard Becker & William S Cleveland," S-Plus Trellis Graphics User's Manual", 1996)

"The illusion of randomness gradually disappears as the skill in chart reading improves." (John W Murphy, "Technical Analysis of the Financial Markets", 1999)

"The binders, the charts, the grids may seem formidable, but the meetings themselves are built around informality, trust, emotion and humor." (Jack Welch, "Jack: Straight from the Gut", 2001)

"A bar graph typically presents either averages or frequencies. It is relatively simple to present raw data (in the form of dot plots or box plots). Such plots provide much more information. and they are closer to the original data. If the bar graph categories are linked in some way - for example, doses of treatments - then a line graph will be much more informative. Very complicated bar graphs containing adjacent bars are very difficult to grasp. If the bar graph represents frequencies. and the abscissa values can be ordered, then a line graph will be much more informative and will have substantially reduced chart junk." (Gerald van Belle, "Statistical Rules of Thumb", 2002)

"A good graph displays relationships and structures that are difficult to detect by merely looking at the data." (Gerald van Belle, "Statistical Rules of Thumb", 2002)

"Stacked bar graphs do not show data structure well. A trend in one of the stacked variables has to be deduced by scanning along the vertical bars. This becomes especially difficult when the categories do not move in the same direction." (Gerald van Belle, "Statistical Rules of Thumb", 2002)

"The most ubiquitous graph is the pie chart. It is a staple of the business world. [...] Never use a pie chart. Present a simple list of percentages, or whatever constitutes the divisions of the pie chart." (Gerald van Belle, "Statistical Rules of Thumb", 2002)

"This pie chart violates several of the rules suggested by the question posed in the introduction. First, immediacy: the reader has to turn to the legend to find out what the areas represent; and the lack of color makes it very difficult to determine which area belongs to what code. Second, the underlying structure of the data is completely ignored. Third, a tremendous amount of ink is used to display eight simple numbers." (Gerald van Belle, "Statistical Rules of Thumb", 2002)

"Always bear in mind that the purposes of any chart are (1) to help gather, organize or visualize the facts; (2) to aid in analyzing them; (3) to help in developing the better method and evaluating it; (4) to assist in convincing management of the improvement’s value." (Ben B Graham, "Detail Process Charting: Speaking the Language of Process", 2004)

"Generally pie charts are to be avoided, as they can be difficult to interpret particularly when the number of categories is greater than five. Small proportions can be very hard to discern […] In addition, unless the percentages in each of the individual categories are given as numbers it can be much more diff i cult to estimate them from a pie chart than from a bar chart […]." (Jenny Freeman et al, "How to Display Data", 2008)

"When displaying information visually, there are three questions one will find useful to ask as a starting point. Firstly and most importantly, it is vital to have a clear idea about what is to be displayed; for example, is it important to demonstrate that two sets of data have different distributions or that they have different mean values? Having decided what the main message is, the next step is to examine the methods available and to select an appropriate one. Finally, once the chart or table has been constructed, it is worth reflecting upon whether what has been produced truly reflects the intended message. If not, then refine the display until satisfied; for example if a chart has been used would a table have been better or vice versa?" (Jenny Freeman et al, "How to Display Data", 2008)

"Where there is no natural ordering to the categories it can be helpful to order them by size, as this can help you to pick out any patterns or compare the relative frequencies across groups. As it can be difficult to discern immediately the numbers represented in each of the categories it is good practice to include the number of observations on which the chart is based, together with the percentages in each category." (Jenny Freeman et al, "How to Display Data", 2008)

"So what is the difference between a chart or graph and a visualization? […] a chart or graph is a clean and simple atomic piece; bar charts contain a short story about the data being presented. A visualization, on the other hand, seems to contain much more ʻchart junkʼ, with many sometimes complex graphics or several layers of charts and graphs. A visualization seems to be the super-set for all sorts of data-driven design." (Brian Suda, "A Practical Guide to Designing with Data", 2010)

"The amount of information rendered in a single financial graph is easily equivalent to thousands of words of text or a page-sized table of raw values. A graph illustrates so many characteristics of data in a much smaller space than any other means. Charts also allow us to tell a story in a quick and easy way that words cannot." (Brian Suda, "A Practical Guide to Designing with Data", 2010) 

"Graphics, charts, and maps aren’t just tools to be seen, but to be read and scrutinized. The first goal of an infographic is not to be beautiful just for the sake of eye appeal, but, above all, to be understandable first, and beautiful after that; or to be beautiful thanks to its exquisite functionality." (Alberto Cairo, "The Functional Art", 2011)

"if you want to show change through time, use a time-series chart; if you need to compare, use a bar chart; or to display correlation, use a scatter-plot - because some of these rules make good common sense." (Alberto Cairo, "The Functional Art", 2011) 

"The overuse of bubble charts in news media is a good example of how infographics departments can become more worried about how their projects look than with how they work." (Alberto Cairo, "The Functional Art", 2011)

"The simplicity of the process behavior chart can be deceptive.  This is because the simplicity of the charts is based on a completely different concept of data analysis than that which is used for the analysis of experimental data.  When someone does not understand the conceptual basis for process behavior charts they are likely to view the simplicity of the charts as something that needs to be fixed.  Out of these urges to fix the charts all kinds of myths have sprung up resulting in various levels of complexity and obstacles to the use of one of the most powerful analysis techniques ever invented." (Donald J Wheeler, "Myths About Data Analysis", International Lean & Six Sigma Conference, 2012)

"Diagrams furnish only approximate information. They do not add anything to the meaning of the data and, therefore, are not of much use to a statistician or research worker for further mathematical treatment or statistical analysis. On the other hand, graphs are more obvious, precise and accurate than the diagrams and are quite helpful to the statistician for the study of slopes, rates of change and estimation, (interpolation and extrapolation), wherever possible." (S C Gupta & Indra Gupta, "Business Statistics", 2013)

"Readability in visualization helps people interpret data and make conclusions about what the data has to say. Embed charts in reports or surround them with text, and you can explain results in detail. However, take a visualization out of a report or disconnect it from text that provides context (as is common when people share graphics online), and the data might lose its meaning; or worse, others might misinterpret what you tried to show." (Nathan Yau, "Data Points: Visualization That Means Something", 2013)

"Visualization is what happens when you make the jump from raw data to bar graphs, line charts, and dot plots. […] In its most basic form, visualization is simply mapping data to geometry and color. It works because your brain is wired to find patterns, and you can switch back and forth between the visual and the numbers it represents. This is the important bit. You must make sure that the essence of the data isn’t lost in that back and forth between visual and the value it represents because if you can’t map back to the data, the visualization is just a bunch of shapes." (Nathan Yau, "Data Points: Visualization That Means Something", 2013)

"Graphs can help us interpret data and draw inferences. They can help us see tendencies, patterns, trends, and relationships. A picture can be worth not only a thousand words, but a thousand numbers. However, a graph is essentially descriptive - a picture meant to tell a story. As with any story, bumblers may mangle the punch line and the dishonest may lie." (Gary Smith, "Standard Deviations", 2014)

"Graphs should not be mere decoration, to amuse the easily bored. A useful graph displays data accurately and coherently, and helps us understand the data. Chartjunk, in contrast, distracts, confuses, and annoys. Chartjunk may be well-intentioned, but it is misguided. It may also be a deliberate attempt to mystify." (Gary Smith, "Standard Deviations", 2014)

"Numbers are not inherently tedious. They can be illuminating, fascinating, even entertaining. The trouble starts when we decide that it is more important for a graph to be artistic than informative." (Gary Smith, "Standard Deviations", 2014)

"If I had to pick a single go-to graph for categorical data, it would be the horizontal bar chart, which flips the vertical version on its side. Why? Because it is extremely easy to read. The horizontal bar chart is especially useful if your category names are long, as the text is written from left to right, as most audiences read, making your graph legible for your audience." (Cole N Knaflic, "Storytelling with Data: A Data Visualization Guide for Business Professionals", 2015)

"Sometimes bar charts are avoided because they are common. This is a mistake. Rather, bar charts should be leveraged because they are common, as this means less of a learning curve for your audience." (Cole N Knaflic, "Storytelling with Data: A Data Visualization Guide for Business Professionals", 2015)

"The unique thing you get with a pie chart is the concept of there being a whole and, thus, parts of a whole. But if the visual is difficult to read, is it worth it?" (Cole N Knaflic, "Storytelling with Data: A Data Visualization Guide for Business Professionals", 2015)

"Charts are always an interpretation of data, in the same way that a photo is an interpretation of reality, no matter how objective it may seem. This should be not only recognized but encouraged within an ethical framework that seeks to identify its own subjectivity and minimize its influence on choices. There can be no contradiction between 'what I want to say' and 'what the data say'. This difference is often difficult to detect, especially when the subject’s message is fully determined by his beliefs, ideological position, and activism." (Jorge Camões, "Data at Work: Best practices for creating effective charts and information graphics in Microsoft Excel", 2016)

"Data stories are a subset of the much broader concept (or buzzword) of storytelling. […] Stories, or narratives, are useful in data visualization because they force us to recognize the limited value of a single chart in a complex environment. Stories also force us to recognize the need for a better integration of our displays, as we move away from strings of siloed charts." (Jorge Camões, "Data at Work: Best practices for creating effective charts and information graphics in Microsoft Excel", 2016)

"The most pragmatic way of beginning the data visualization process is with a question, and then making a chart that answers that question. […] Certain charts are better suited to answer certain questions than others, but you should take this relationship as a broad principle. Subtle changes in the question and in the chart design can impact the results. Having a clear goal in mind and knowing what type of visualization could be more effective can help us reduce the range of options of chart types and design choices." (Jorge Camões, "Data at Work: Best practices for creating effective charts and information graphics in Microsoft Excel", 2016)

"When we use the number of dimensions as the classification criterion of visual displays, we get four distinct groups: charts, networks, and maps, along with figurative visualizations as a special group." (Jorge Camões, "Data at Work: Best practices for creating effective charts and information graphics in Microsoft Excel", 2016)

"Creating effective visualizations is hard. Not because a dataset requires an exotic and bespoke visual representation - for many problems, standard statistical charts will suffice. And not because creating a visualization requires coding expertise in an unfamiliar programming language [...]. Rather, creating effective visualizations is difficult because the problems that are best addressed by visualization are often complex and ill-formed. The task of figuring out what attributes of a dataset are important is often conflated with figuring out what type of visualization to use. Picking a chart type to represent specific attributes in a dataset is comparatively easy. Deciding on which data attributes will help answer a question, however, is a complex, poorly defined, and user-driven process that can require several rounds of visualization and exploration to resolve." (Danyel Fisher & Miriah Meyer, "Making Data Visual", 2018)

"Analysis is a two-step process that has an exploratory and an explanatory phase. In order to create a powerful data story, you must effectively transition from data discovery (when you’re finding insights) to data communication (when you’re explaining them to an audience). If you don’t properly traverse these two phases, you may end up with something that resembles a data story but doesn’t have the same effect. Yes, it may have numbers, charts, and annotations, but because it’s poorly formed, it won’t achieve the same results." (Brent Dykes, "Effective Data Storytelling: How to Drive Change with Data, Narrative and Visuals", 2019)

"When visuals are applied to data, they can enlighten the audience to insights that they wouldn’t see without charts or graphs. Many interesting patterns and outliers in the data would remain hidden in the rows and columns of data tables without the help of data visualizations. They connect with our visual nature as human beings and impart knowledge that couldn’t be obtained as easily using other approaches that involve just words or numbers." (Brent Dykes, "Effective Data Storytelling: How to Drive Change with Data, Narrative and Visuals", 2019)

"While visuals are an essential part of data storytelling, data visualizations can serve a variety of purposes from analysis to communication to even art. Most data charts are designed to disseminate information in a visual manner. Only a subset of data compositions is focused on presenting specific insights as opposed to just general information. When most data compositions combine both visualizations and text, it can be difficult to discern whether a particular scenario falls into the realm of data storytelling or not." (Brent Dykes, "Effective Data Storytelling: How to Drive Change with Data, Narrative and Visuals", 2019)

"Aligning on data ink can be a powerful way to build relationships across charts. It can be used to obscure the lines between charts, making the composition feel more seamless. [....] Alignment paradigms can also influence the layout design needed. [...] The layout added to the alignment further supports this relationship." (Vidya Setlur & Bridget Cogley, "Functional Aesthetics for data visualization", 2022)

"Beyond basic charts, practitioners must also learn to compose visualizations together elegantly. The perceptual stage focuses on making the literal charts more precise as well as working to de-emphasize the entire piece. Design choices start to consider distractions, reducing visual clutter and centering on the message. Minimalism is espoused as a core value with an emphasis on shifting toward precision as accuracy. This is the most common next step for practitioners. Minimalism is also a key stage in maturation. It is experimentation at one extreme that helps practitioners distill down to core, shared practices." (Vidya Setlur & Bridget Cogley, "Functional Aesthetics for data visualization", 2022)

"Beyond the design of individual charts, the sequence of data visualizations creates grammar within the exposition. Cohesive visualizations follow common narrative structures to fully express their message. Order matters."  (Vidya Setlur & Bridget Cogley, "Functional Aesthetics for data visualization", 2022)

"Like multimodal reading, data literacy relies on both primary literacy skills and numeracy skills to truly make sense of the third layer: reading and understanding graphs. Charts codify numbers visually into parameters, using stylized marks to embed additional layers of meaning and space to provide quantitative relationships. Beyond the individual chart, data visualizations create ensembles of charts." (Vidya Setlur & Bridget Cogley, "Functional Aesthetics for data visualization", 2022)

"The sizes of charts in space reflect how we convey information to a reader. In a dashboard context, the content, size, and space that the various charts occupy should reflect the form and function of the main message. As you saw with the bento box metaphor from the introduction, there needs to be deliberate thought put into the placement and size of each individual chart so that they all work together in harmony." (Vidya Setlur & Bridget Cogley, "Functional Aesthetics for data visualization", 2022)

"[...] to support a conversation, charts need to provide cohesive and relevant responses to a user's intent. Sometimes the interface needs to respond by changing the visual encoding of existing charts, while in other cases, it is necessary to create a new chart to support the analytical conversation. In addition to appropriate visualization responses, it is critical to help the user understand how the system has interpreted their intent by producing appropriate feedback and allowing them to clarify if necessary." (Vidya Setlur & Bridget Cogley, "Functional Aesthetics for data visualization", 2022)

"Charts used to confirm are less formal, and designed well enough to be interpreted, but they don’t always have to be presentation worthy. […] Or maybe you don’t know what you’re looking for […] This is exploratory work - rougher still in design, usually iterative, sometimes interactive. Most of us don’t do as much exploratory work as we do declarative and confirmatory; we should do more. It’s a kind of data brainstorming." (Scott Berinato, "Good Charts : the HBR guide to making smarter, more persuasive data visualizations", 2023)

"In general, charts that contain enough data to take minutes, not seconds, to digest will work better on paper or a personal screen, for an individual who’s not being asked to listen to a presentation while trying to take in so much information." (Scott Berinato, "Good Charts : the HBR guide to making smarter, more persuasive data visualizations", 2023)

"We see first what stands out. Our eyes go right to change and difference - peaks, valleys, intersections, dominant colors, outliers. Many successful charts - often the ones that please us the most and are shared and talked about - exploit this inclination by showing a single salient point so clearly that we feel we understand the chart’s meaning without even trying." (Scott Berinato, "Good Charts : the HBR guide to making smarter, more persuasive data visualizations", 2023)