On Construction VII: Mental Models

"Physics is the attempt at the conceptual construction of a model of the real world and its lawful structure." (Albert Einstein, [letter to Moritz Schlick] 1931)

"[…] the process of scientific discovery may be regarded as a form of art. This is best seen in the theoretical aspects of Physical Science. The mathematical theorist builds up on certain assumptions and according to well understood logical rules, step by step, a stately edifice, while his imaginative power brings out clearly the hidden relations between its parts. A well-constructed theory is in some respects undoubtedly an artistic production." (Ernest Rutherford, 1932)

"In the realm of physics it is perhaps only the theory of relativity which has made it quite clear that the two essences, space and time, entering into our intuition, have no place in the world constructed by mathematical physics. Colours are thus 'really' not even æther-vibrations, but merely a series of values of mathematical functions in which occur four independent parameters corresponding to the three dimensions of space, and the one of time." (Hermann Weyl, "Space, Time, Matter", 1952)

"In physics it is usual to give alternative theoretical treatments of the same phenomenon. We construct different models for different purposes, with different equations to describe them. Which is the right model, which the 'true' set of equations? The question is a mistake. One model brings out some aspects of the phenomenon; a different model brings out others. Some equations give a rougher estimate for a quantity of interest, but are easier to solve. No single model serves all purposes best." (Nancy Cartwright, "How the Laws of Physics Lie", 1983)

"Physics is like that. It is important that the models we construct allow us to draw the right conclusions about the behaviour of the phenomena and their causes. But it is not essential that the models accurately describe everything that actually happens; and in general it will not be possible for them to do so, and for much the same reasons. The requirements of the theory constrain what can be literally represented. This does not mean that the right lessons cannot be drawn. Adjustments are made where literal correctness does not matter very much in order to get the correct effects where we want them; and very often, as in the staging example, one distortion is put right by another. That is why it often seems misleading to say that a particular aspect of a model is false to reality: given the other constraints that is just the way to restore the representation." (Nancy Cartwright, "How the Laws of Physics Lie", 1983)

"[…] most earlier attempts to construct a theory of complexity have overlooked the deep link between it and networks. In most systems, complexity starts where networks turn nontrivial. No matter how puzzled we are by the behavior of an electron or an atom, we rarely call it complex, as quantum mechanics offers us the tools to describe them with remarkable accuracy. The demystification of crystals-highly regular networks of atoms and molecules-is one of the major success stories of twentieth-century physics, resulting in the development of the transistor and the discovery of superconductivity. Yet, we continue to struggle with systems for which the interaction map between the components is less ordered and rigid, hoping to give self-organization a chance." (Albert-László Barabási, "Linked: How Everything Is Connected to Everything Else and What It Means for Business, Science, and Everyday Life", 2002)

"Just as physicists have created models of the atom based on observed data and intuitive synthesis of the patterns in their data, so must designers create models of users based on observed behaviors and intuitive synthesis of the patterns in the data. Only after we formalize such patterns can we hope to systematically construct patterns of interaction that smoothly match the behavior patterns, mental models, and goals of users. Personas provide this formalization." (Alan Cooper et al, "About Face 3: The Essentials of Interaction Design", 2007)

"There are actually two sides to the success of mathematics in explaining the world around us (a success that Wigner dubbed ‘the unreasonable effectiveness of mathematics’), one more astonishing than the other. First, there is an aspect one might call ‘active’. When physicists wander through nature’s labyrinth, they light their way by mathematics - the tools they use and develop, the models they construct, and the explanations they conjure are all mathematical in nature. This, on the face of it, is a miracle in itself. […] But there is also a ‘passive’ side to the mysterious effectiveness of mathematics, and it is so surprising that the 'active' aspect pales by comparison. Concepts and relations explored by mathematicians only for pure reasons - with absolutely no application in mind—turn out decades (or sometimes centuries) later to be the unexpected solutions to problems grounded in physical reality!" (Mario Livio, "Is God a Mathematician?", 2011)

On Construction VIII: Science

"Science gains from it [the pendulum] more than one can expect. With its huge dimensions, the apparatus presents qualities that one would try in vain to communicate by constructing it on a small [scale], no matter how carefully. Already the regularity of its motion promises the most conclusive results. One collects numbers that, compared with the predictions of theory, permit one to appreciate how far the true pendulum approximates or differs from the abstract system called 'the simple pendulum'." (Jean-Bernard-Léon Foucault, "Demonstration Experimentale du Movement de Rotation de la Terre", 1851)

"The invention of a new symbol is a step in the advancement of civilisation. Why were the Greeks, in spite of their penetrating intelligence and their passionate pursuit of Science, unable to carry Mathematics farther than they did? and why, having formed the conception of the Method of Exhaustions, did they stop short of that of the Differential Calculus? It was because they had not the requisite symbols as means of expression. They had no Algebra. Nor was the place of this supplied by any other symbolical language sufficiently general and flexible; so that they were without the logical instruments necessary to construct the great instrument of the Calculus." (George H Lewes "Problems of Life and Mind", 1873)

"We shall call this universal organizational science the 'Tektology'. The literal translation of this word from the Greek is 'the theory of construction'. 'Construction' is the most generaI and suitable synonym for the modern concept of 'organization'. [...] The aim of tektology is to systematize organizational experience; this science is clearly empirical and should draw its conclusions by way of induction." (Alexander Bogdanov, "Tektology: The Universal Organizational Science" Vol. I, 1913)

"It would be a mistake to suppose that a science consists entirely of strictly proved theses, and it would be unjust to require this. […] Science has only a few apodeictic propositions in its catechism: the rest are assertions promoted by it to some particular degree of probability. It is actually a sign of a scientific mode of thought to find satisfaction in these approximations to certainty and to be able to pursue constructive work further in spite of the absence of final confirmation." (Sigmund Freud, "Introductory Lectures on Psycho-Analysis", 1916)

"Science is a magnificent force, but it is not a teacher of morals. It can perfect machinery, but it adds no moral restraints to protect society from the misuse of the machine. It can also build gigantic intellectual ships, but it constructs no moral rudders for the control of storm tossed human vessel. It not only fails to supply the spiritual element needed but some of its unproven hypotheses rob the ship of its compass and thus endangers its cargo." (William J Bryan, "Undelivered Trial Summation Scopes Trial", 1925)

"Science aims at constructing a world which shall be symbolic of the world of commonplace experience." (Sir Arthur S Eddington, "The Nature of the Physical World", 1928)

"No doctrinal system in physical science, or indeed perhaps in any science, will alter its content of its own accord. Here we always need the pressure of outer circumstances. Indeed the more intelligible and comprehensive a theoretical system is the more obstinately it will resist all attempts at reconstruction or expansion." (Max Planck, "Where is Science Going?", 1932)

"A scientist, whether theorist or experimenter, puts forward statements, or systems of statements, and tests them step by step. In the field of the empirical sciences, more particularly, he constructs hypotheses, or systems of theories, and tests them against experience by observation and experiment." (Karl Popper, "The Logic of Scientific Discovery", 1934)

"Mathematics as an expression of the human mind reflects the active will, the contemplative reason, and the desire for aesthetic perfection. Its basic elements are logic and intuition, analysis and construction, generality and individuality. Though different traditions may emphasize different aspects, it is only the interplay of these antithetic forces and the struggle for their synthesis that constitute the life, usefulness, and supreme value of mathematical science." (Richard Courant & Herbert Robbins, "What Is Mathematics?", 1941)

"A theoretical science unaware that those of its constructs considered relevant and momentous are destined eventually to be framed in concepts and words that have a grip on the educated community and become part and parcel of the general world picture - a theoretical science [...]" (Erwin Schrödinger, "Are There Quantum Jumps?", The British Journal for the Philosophy of Science Vol. 3, 1952)

"[...] sciences do not try to explain, they hardly even try to interpret, they mainly make models. By a model is meant a mathematical construct which, with the addition of certain verbal interpretations, describes observed phenomena. The justification of such a mathematical construct is solely and precisely that it is expected to work - that is, correctly to describe phenomena from a reasonably wide area. Furthermore, it must satisfy certain aesthetic criteria - that is, in relation to how much it describes, it must be rather simple." (John von Neumann, "Method in the physical sciences", 1955)

"We realize, however, that all scientific laws merely represent abstractions and idealizations expressing certain aspects of reality. Every science means a schematized picture of reality, in the sense that a certain conceptual construct is unequivocally related to certain features of order in reality […]" (Ludwig von Bertalanffy, "General System Theory", 1968)

"Many people believe that reasoning, and therefore science, is a different activity from imagining. But this is a fallacy […] Reasoning is constructed with movable images just as certainly as poetry is." (Jacob Bronowski, "Visionary Eye", 1978)

"[…] the pursuit of science is more than the pursuit of understanding. It is driven by the creative urge, the urge to construct a vision, a map, a picture of the world that gives the world a little more beauty and coherence than it had before." (John A Wheeler, "Geons, Black Holes, and Quantum Foam: A Life in Physics", 1998)

On Constructs VII - Mind

"Ideas are substitutions which require a secondary process when what is symbolized by them is translated into the images and experiences it replaces; and this secondary process is frequently not performed at all, generally only performed to a very small extent. Let anyone closely examine what has passed in his mind when he has constructed a chain of reasoning, and he will be surprised at the fewness and faintness of the images which have accompanied the ideas." (George H Lewes "Problems of Life and Mind", 1873)

"The mind of man, learning consciously and unconsciously lessons of experience, gradually constructs a mental image of its surroundings - as the mariner draws a chart of strange coasts to guide him in future voyages, and to enable those that follow after him to sail the same seas with ease and safety." (William C Dampier, "The Recent Development of Physical Science", 1904)

"[…] we can only study Nature through our senses - that is […] we can only study the model of Nature that our senses enable our minds to construct; we cannot decide whether that model, consistent though it be, represents truly the real structure of Nature; whether, indeed, there be any Nature as an ultimate reality behind its phenomena." (William C Dampier, "The Recent Development of Physical Science", 1904)

"While the stuff from which our world picture is build is yielded exclusively from the sense organs as organs of the mind, so that every man's world picture is and always remains a construct of his mind and cannot be proved to have any other existence […]" (Erwin Schrodinger, "What is Life?", 1944)

"Science begins with the world we have to live in, accepting its data and trying to explain its laws. From there, it moves toward the imagination: it becomes a mental construct, a model of a possible way of interpreting experience." (Northrop Frye, "The Educated Imagination", 1964)

"We never have any understanding of any subject matter except in terms of our own mental constructs of 'things' and 'happenings' of that subject matter." (Douglas T Ross, "Structured analysis (SA): A language for communicating ideas", IEEE Transactions on Software Engineering Vol. 3 (1), 1977)

"Perhaps we all lose our sense of reality to the precise degree to which we are engrossed in our own work, and perhaps that is why we see in the increasing complexity of our mental constructs a means for greater understanding, even while intuitively we know that we shall never be able to fathom the imponderables that govern our course through life." (Winfried G Sebald, "The Rings of Saturn", 1995)

"The seemingly stable scene you normally see is really a mental model that you construct - the eyes are actually darting all around, producing a retinal image as jerky as an amateur video, and some of what you thought you saw was instead filled in from memory." (William H Calvin, "How Brains Think", 1996)

"A general limitation of the human mind is its imperfect ability to reconstruct past states of knowledge, or beliefs that have changed. Once you adopt a new view of the world (or any part of it), you immediately lose much of your ability to recall what you used to believe before your mind changed." (Daniel Kahneman, "Thinking, Fast and Slow", 2011)

Abraham Kaplan - Collected Quotes

"By and large, then, the important terms of any science are significant because of their semantics, not their syntax: they are not notational, but reach out to the world which gives the science its subject-matter. The meaning of such terms results rom a process of conceptualization of the subject-matter." (Abraham Kaplan, "The Conduct of Inquiry: Methodology for Behavioral Science", 1964)

"Concepts, then, mark out the paths by which we may move most freely in the logical space. They identify nodes or junctions in the network of relationships, termini at which we can halt while preserving the maximum range of choice as to where to go next." (Abraham Kaplan, "The Conduct of Inquiry: Methodology for Behavioral Science", 1964)

"Constructs are terms which, though not observational either directly or indirectly, may be applied and even defined on the basis of the observables. [...] Constructs, in other words, have systemic as well as observational meaning specified by horizontal rather than vertical connections Strictly speaking, the difference between constructs and theoretical terms can be localized in the nature of vertical connections alone:  for constructs the relation to observations is definitional, while for theoretical terms it is a matter of empirical fact." (Abraham Kaplan, "The Conduct of Inquiry: Methodology for Behavioral Science", 1964)

"Give a small boy a hammer, and he will find that everything he encounters needs pounding. It comes as no particular surprise to discover that a scientist formulates problems in a way which requires for their solution just those techniques in which he himself is especially skilled." (Abraham Kaplan, "The Conduct of Inquiry: Methodology for Behavioral Science", 1964)

"In consequence, we are caught up in a paradox, one which might be called the paradox of conceptualization. The proper concepts are needed to formulate a good theory, but we need a good theory to arrive at the proper concepts." (Abraham Kaplan, "The Conduct of Inquiry: Methodology for Behavioral Science", 1964)

"Measurement, we have seen, always has an element of error in it. The most exact description or prediction that a scientist can make is still only approximate." (Abraham Kaplan, "The Conduct of Inquiry: Methodology for Behavioral Science", 1964)

"Methods are techniques sufficient general to be common to all sciences, or to a significant part of them. Alternatively, they are logical or philosophical principles sufficiently specific to relate especially to science as distinguished from other human enterprises and interests. Thus, methods include such procedures as forming concepts and hypotheses making observations and measurements, performing experiments, building models and theories, providing explanations, and making predictions. The aim of methodology, then, is to describe and analyze these methods, throwing light on their limitations and resources, clarifying their presupposition and consequences, relating their potentialities to the twilight zone at the frontiers of knowledge." (Abraham Kaplan, "The Conduct of Inquiry: Methodology for Behavioral Science", 1964)

"[…] statistical techniques are tools of thought, and not substitutes for thought." (Abraham Kaplan, "The Conduct of Inquiry: Methodology for Behavioral Science", 1964)

"The autonomy of inquiry is in no way incompatible with the mature dependency of the several sciences on one another. Nor does this autonomy imply that the individual scientist is accountable only to himself." (Abraham Kaplan, "The Conduct of Inquiry: Methodology for Behavioral Science", 1964)

"We are caught up in a paradox, one which might be called the paradox of conceptualization. The proper concepts are needed to formulate a good theory, but we need a good theory to arrive at the proper concepts." (Abraham Kaplan, "The Conduct of Inquiry: Methodology for Behavioral Science", 1964)

"What knowledge requires of experience, and what experience provides, is an independence of our mere think-so. The pleasure principle governing the life of the infant gives way to the reality principle as wishes encounter obstacles to their fulfilment. The word 'object', it has been said, can be understood as referring to that which objects. That is objective which insists on its own rights regardless of our wishes, and only experience can transmit its claims to us." (Abraham Kaplan, "The Conduct of Inquiry: Methodology for Behavioral Science", 1964)

"What we call 'intuition' is any logic-in-use which is (1) preconscious, and (2) outside the inference schema for which we reconstructions. We speak of intuition, in short, M hen neither we nor the discoverer himself knows quite how he arrives at his discoveries, while the frequency or pattern of their occurrence makes us reluctant to ascribe them merely to chance." (Abraham Kaplan, "The Conduct of Inquiry: Methodology for Behavioral Science", 1964)

Book available in the Internet Archive.

From Parts to Wholes (1980-1989)

"The principle that whole entities exhibit properties which are meaningful only when attributed to the whole, not to its parts - e.g. the smell of ammonia. Every model of human activity system exhibits properties as a whole entity which derive from it component activities and their structure, but cannot be reduced to them." (Peter Checkland, "Systems Thinking, Systems Practice", 1981)

"[Hierarchy is] the principle according to which entities meaningfully treated as wholes are built up of smaller entities which are themselves wholes […] and so on. In hierarchy, emergent properties denote the levels." (Peter Checkland, "Systems Thinking, Systems Practice", 1981)

"Degradation of a system as a whole does not mean that all its elements are beginning to disintegrate. Regress is a contradictory process: the whole falls apart but certain elements in it may progress. What is more, a system as a whole may progress while certain of its elements fall into decay. Thus, the progressive development of biological forms as a whole goes hand in hand with the degradation of certain species." (Alexander Spirkin, "Dialectical Materialism", 1983)

"Structure is the type of connection between the elements of a whole. […] . Structure is a composite whole, or an internally organised content. […] Structure implies not only the position of its elements in space but also their movement in time, their sequence and rhythm, the law of mutation of a process. So structure is actually the law or set of laws that determine a system's composition and functioning, its properties and stability." (Alexander Spirkin, "Dialectical Materialism", 1983)

"The defining attribute of harmony is a relationship between the elements of the whole in which the development of one of them is a condition for the development of the others or vice versa. In art, harmony may be understood as a form of relationship in which each element, while retaining a relative independence, contributes greater expressiveness to the whole and, at the same time and because of this, more fully expresses its own essence. Beauty may be defined as harmony of all the parts, united by that to which they belong in such a way that nothing can be added or taken away or changed without detriment to the whole." (Alexander Spirkin, "Dialectical Materialism", 1983)

On Numbers: Large Numbers II

"A good description of the data summarizes the systematic variation and leaves residuals that look structureless. That is, the residuals exhibit no patterns and have no exceptionally large values, or outliers. Any structure present in the residuals indicates an inadequate fit. Looking at the residuals laid out in an overlay helps to spot patterns and outliers and to associate them with their source in the data." (Christopher H Schrnid, "Value Splitting: Taking the Data Apart", 1991)

"Skewness is a measure of symmetry. For example, it's zero for the bell-shaped normal curve, which is perfectly symmetric about its mean. Kurtosis is a measure of the peakedness, or fat-tailedness, of a distribution. Thus, it measures the likelihood of extreme values." (John L Casti, "Reality Rules: Picturing the world in mathematics", 1992)

"Data that are skewed toward large values occur commonly. Any set of positive measurements is a candidate. Nature just works like that. In fact, if data consisting of positive numbers range over several powers of ten, it is almost a guarantee that they will be skewed. Skewness creates many problems. There are visualization problems. A large fraction of the data are squashed into small regions of graphs, and visual assessment of the data degrades. There are characterization problems. Skewed distributions tend to be more complicated than symmetric ones; for example, there is no unique notion of location and the median and mean measure different aspects of the distribution. There are problems in carrying out probabilistic methods. The distribution of skewed data is not well approximated by the normal, so the many probabilistic methods based on an assumption of a normal distribution cannot be applied." (William S Cleveland, "Visualizing Data", 1993)

"The logarithm is one of many transformations that we can apply to univariate measurements. The square root is another. Transformation is a critical tool for visualization or for any other mode of data analysis because it can substantially simplify the structure of a set of data. For example, transformation can remove skewness toward large values, and it can remove monotone increasing spread. And often, it is the logarithm that achieves this removal." (William S Cleveland, "Visualizing Data", 1993)

"Factoring big numbers is a strange kind of mathematics that closely resembles the experimental sciences, where nature has the last and definitive word. […] as with the experimental sciences, both rigorous and heuristic analyses can be valuable in understanding the subject and moving it forward. And, as with the experimental sciences, there is sometimes a tension between pure and applied practitioners." (Carl B Pomerance, "A Tale of Two Sieves", The Notices of the American Mathematical Society 43, 1996)

"Clearly, the mean is greatly influenced by extreme values, but it can be appropriate for many situations where extreme values do not arise. To avoid misuse, it is essential to know which summary measure best reflects the data and to use it carefully. Understanding the situation is necessary for making the right choice. Know the subject!" (Herbert F Spirer et al, "Misused Statistics" 2nd Ed, 1998)

"Big numbers warn us that the problem is a common one, compelling our attention, concern, and action. The media like to report statistics because numbers seem to be 'hard facts' - little nuggets of indisputable truth. [...] One common innumerate error involves not distinguishing among large numbers. [...] Because many people have trouble appreciating the differences among big numbers, they tend to uncritically accept social statistics (which often, of course, feature big numbers)." (Joel Best, "Damned Lies and Statistics: Untangling Numbers from the Media, Politicians, and Activists", 2001)

"Use a logarithmic scale when it is important to understand percent change or multiplicative factors. […] Showing data on a logarithmic scale can cure skewness toward large values." (Naomi B Robbins, "Creating More effective Graphs", 2005) 

"Outliers or influential data points can be defined as data values that are extreme or atypical on either the independent (X variables) or dependent (Y variables) variables or both. Outliers can occur as a result of observation errors, data entry errors, instrument errors based on layout or instructions, or actual extreme values from self-report data. Because outliers affect the mean, the standard deviation, and correlation coefficient values, they must be explained, deleted, or accommodated by using robust statistics." (Randall E Schumacker & Richard G Lomax, "A Beginner’s Guide to Structural Equation Modeling" 3rd Ed., 2010)

"Comparisons are the lifeblood of empirical studies. We can’t determine if a medicine, treatment, policy, or strategy is effective unless we compare it to some alternative. But watch out for superficial comparisons: comparisons of percentage changes in big numbers and small numbers, comparisons of things that have nothing in common except that they increase over time, comparisons of irrelevant data. All of these are like comparing apples to prunes." (Gary Smith, "Standard Deviations", 2014)

"It is not enough to give a single summary for a distribution - we need to have an idea of the spread, sometimes known as the variability. [...] The range is a natural choice, but is clearly very sensitive to extreme values [...] In contrast the inter-quartile range (IQR) is unaffected by extremes. This is the distance between the 25th and 75th percentiles of the data and so contains the ‘central half’ of the numbers [...] Finally the standard deviation is a widely used measure of spread. It is the most technically complex measure, but is only really appropriate for well-behaved symmetric data since it is also unduly influenced by outlying values." (David Spiegelhalter, "The Art of Statistics: Learning from Data", 2019)

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On Statisticians (2000 -)

 "Things are changing. Statisticians now recognize that computer scientists are making novel contributions while computer scientists now recognize the generality of statistical theory and methodology. Clever data mining algorithms are more scalable than statisticians ever thought possible. Formal statistical theory is more pervasive than computer scientists had realized." (Larry A Wasserman, "All of Statistics: A concise course in statistical inference", 2004

"[...] statisticians are constantly looking out for missed nuances: a statistical average for all groups may well hide vital differences that exist between these groups. Ignoring group differences when they are present frequently portends inequitable treatment." (Kaiser Fung, "Numbers Rule the World", 2010)

"What is so unconventional about the statistical way of thinking? First, statisticians do not care much for the popular concept of the statistical average; instead, they fixate on any deviation from the average. They worry about how large these variations are, how frequently they occur, and why they exist. [...] Second, variability does not need to be explained by reasonable causes, despite our natural desire for a rational explanation of everything; statisticians are frequently just as happy to pore over patterns of correlation. [...] Third, statisticians are constantly looking out for missed nuances: a statistical average for all groups may well hide vital differences that exist between these groups. Ignoring group differences when they are present frequently portends inequitable treatment. [...] Fourth, decisions based on statistics can be calibrated to strike a balance between two types of errors. Predictably, decision makers have an incentive to focus exclusively on minimizing any mistake that could bring about public humiliation, but statisticians point out that because of this bias, their decisions will aggravate other errors, which are unnoticed but serious. [...] Finally, statisticians follow a specific protocol known as statistical testing when deciding whether the evidence fits the crime, so to speak. Unlike some of us, they don’t believe in miracles. In other words, if the most unusual coincidence must be contrived to explain the inexplicable, they prefer leaving the crime unsolved." (Kaiser Fung, "Numbers Rule the World", 2010)

"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)

"Good design is an important part of any visualization, while decoration (or chart-junk) is best omitted. Statisticians should also be careful about comparing themselves to artists and designers; our goals are so different that we will fare poorly in comparison." (Hadley Wickham, "Graphical Criticism: Some Historical Notes", Journal of Computational and Graphical Statistics Vol. 22(1), 2013) 

"Missing data is the blind spot of statisticians. If they are not paying full attention, they lose track of these little details. Even when they notice, many unwittingly sway things our way. Most ranking systems ignore missing values." (Kaiser Fung, "Numbersense: How To Use Big Data To Your Advantage", 2013)

"Statisticians set a high bar when they assign a cause to an effect. [...] A model that ignores cause–effect relationships cannot attain the status of a model in the physical sciences. This is a structural limitation that no amount of data - not even Big Data - can surmount." (Kaiser Fung, "Numbersense: How To Use Big Data To Your Advantage", 2013)

"When statisticians, trained in math and probability theory, try to assess likely outcomes, they demand a plethora of data points. Even then, they recognize that unless it’s a very simple and controlled action such as flipping a coin, unforeseen variables can exert significant influence." (Zachary Karabell, "The Leading Indicators: A short history of the numbers that rule our world", 2014)

"Optimization is more than finding the best simulation results. It is itself a complex and evolving field that, subject to certain information constraints, allows data scientists, statisticians, engineers, and traders alike to perform reality checks on modeling results." (Chris Conlan, "Automated Trading with R: Quantitative Research and Platform Development", 2016)

"The tricky part is that there aren’t really any hard- and- fast rules when it comes to identifying outliers. Some economists say an outlier is anything that’s a certain distance away from the mean, but in practice it’s fairly subjective and open to interpretation. That’s why statisticians spend so much time looking at data on a case-by-case basis to determine what is - and isn’t - an outlier." (John H Johnson & Mike Gluck, "Everydata: The misinformation hidden in the little data you consume every day", 2016)

"The job of the statistician is to formulate an inventory of all those things that matter in order to obtain a representative sample. Researchers have to avoid the tendency to capture variables that are easy to identify or collect data on - sometimes the things that matter are not obvious or are difficult to measure." (Daniel J Levitin, "Weaponized Lies", 2017)

"To be any good, a sample has to be representative. A sample is representative if every person or thing in the group you’re studying has an equally likely chance of being chosen. If not, your sample is biased. […] The job of the statistician is to formulate an inventory of all those things that matter in order to obtain a representative sample. Researchers have to avoid the tendency to capture variables that are easy to identify or collect data on - sometimes the things that matter are not obvious or are difficult to measure." (Daniel J Levitin, "Weaponized Lies", 2017)

"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)

"Statisticians are sometimes dismissed as bean counters. The sneering term is misleading as well as unfair. Most of the concepts that matter in policy are not like beans; they are not merely difficult to count, but difficult to define. Once you’re sure what you mean by 'bean', the bean counting itself may come more easily. But if we don’t understand the definition, then there is little point in looking at the numbers. We have fooled ourselves before we have begun."(Tim Harford, "The Data Detective: Ten easy rules to make sense of statistics", 2020)

Alfred R Ilersic - Collected Quotes

"Diagrams are sometimes used, not merely to convey several pieces of information such as several time series on one chart, but also to provide visual evidence of relationships between the series." (Alfred R Ilersic, "Statistics", 1959)

"Everybody has some idea of the meaning of the term 'probability' but there is no agreement among scientists on a precise definition of the term for the purpose of scientific methodology. It is sufficient for our purpose, however, if the concept is interpreted in terms of relative frequency, or more simply, how many times a particular event is likely to occur in a large population." (Alfred R Ilersic, "Statistics", 1959)

"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)

"In brief, the greatest care must be exercised in using any statistical data, especially when it has been collected by another agency. At all times, the statistician who uses published data must ask himself, by whom were the data collected, how and for what purpose?" (Alfred R Ilersic, "Statistics", 1959)

"It is a good rule to remember that the first step in analyzing any statistical data, whether it be culled from an official publication or a report prepared by someone else, is to check the definitions used for classification." (Alfred R Ilersic, "Statistics", 1959)

"It is helpful to remember when dealing with index numbers that they are specialized tools and as such are most efficient and useful when properly used. A screwdriver is a poor substitute for a chisel, although it may be used as such. All index numbers are designed to measure particular groups of related changes." (Alfred R Ilersic, "Statistics", 1959)

"Most people tend to think of values and quantities expressed in numerical terms as being exact figures; much the same as the figures which appear in the trading account of a company. It therefore comes as a considerable surprise to many to learn that few published statistics, particularly economic and sociological data, are exact. Many published figures are only approximations to the real value, while others are estimates of aggregates which are far too large to be measured with precision." (Alfred R Ilersic, "Statistics", 1959)

"Numerical data, which have been recorded at intervals of time, form what is generally described as a time series. [...] The purpose of analyzing time series is not always the determination of the trend by itself. Interest may be centered on the seasonal movement displayed by the series and, in such a case, the determination of the trend is merely a stage in the process of measuring and analyzing the seasonal variation. If a regular basic or under- lying seasonal movement can be clearly established, forecasting of future movements becomes rather less a matter of guesswork and more a matter of intelligent forecasting." (Alfred R Ilersic, "Statistics", 1959)

"Often, in order to simplify statistical tables, the practice of rounding large figures and totals is resorted to. Where the constituent figures in a table together with their aggregate have been so treated, a discrepancy between the rounded total and the true sum of the rounded constituent figures frequently arises. Under no circumstances should the total be adjusted to what appears to be the right answer. A note to the table to the effect that the figures have been rounded, e.g. to the nearest 1,000, is all that is necessary. The same remark applies to percentage equivalents of the constituent parts of a total; it they do not add to exactly 100 per cent, leave them." (Alfred R Ilersic, "Statistics", 1959)

"Poor statistics may be attributed to a number of causes. There are the mistakes which arise in the course of collecting the data, and there are those which occur when those data are being converted into manageable form for publication. Still later, mistakes arise because the conclusions drawn from the published data are wrong. The real trouble with errors which arise during the course of collecting the data is that they are the hardest to detect." (Alfred R Ilersic, "Statistics", 1959)

"Statistical method consists of two main operations; counting and analysis. [...] The statistician has no use for information that cannot be expressed numerically, nor generally speaking, is he interested in isolated events or examples. The term 'data  is itself plural and the statistician is concerned with the analysis of aggregates. " (Alfred R Ilersic, "Statistics", 1959)

"The averaging of percentages themselves requires care, where the percentages are each computed on different bases, i.e. different quantities. The average is not derived by aggregating the percentages and dividing them. Instead of this, each percentage must first be multiplied by its base to bring out its relative significance to the other percentages and to the total. The sum of the resultant products is then divided by the sum of the base values [...], not merely the number of items." (Alfred R Ilersic, "Statistics", 1959)

"The rounding of individual values comprising an aggregate can give rise to what are known as unbiased or biased errors. [...]The biased error arises because all the individual figures are reduced to the lower 1,000 [...] The unbiased error is so described since by rounding each item to the nearest 1,000 some of the approximations are greater and some smaller than the original figures. Given a large number of such approximations, the final total may therefore correspond very closely to the true or original total, since the approximations tend to offset each other. [...] With biased approximations, however, the errors are cumulative and their aggregate increases with the number of items in the series." (Alfred R Ilersic, "Statistics", 1959)

"The simplest way of indicating that figures are not given precisely to the last unit is to express them to the nearest 100 or 1,000; or in some cases to the nearest 100,000 or million. [...] The widespread desire for precision is reflected in many reports on economic trends which quote figures in great detail, rather than emphasizing the trends and movements reflected in the figures." (Alfred R Ilersic, "Statistics", 1959)

"The statistician has no use for information that cannot be expressed numerically, nor generally speaking, is he interested in isolated events or examples. The term ' data ' is itself plural and the statistician is concerned with the analysis of aggregates." (Alfred R Ilersic, "Statistics", 1959)

"The statistics themselves prove nothing; nor are they at any time a substitute for logical thinking. There are […] many simple but not always obvious snags in the data to contend with. Variations in even the simplest of figures may conceal a compound of influences which have to be taken into account before any conclusions are drawn from the data." (Alfred R Ilersic, "Statistics", 1959)

"There are good statistics and bad statistics; it may be doubted if there are many perfect data which are of any practical value. It is the statistician's function to discriminate between good and bad data; to decide when an informed estimate is justified and when it is not; to extract the maximum reliable information from limited and possibly biased data." (Alfred R Ilersic, "Statistics", 1959)

"This is the essential characteristic of a logarithmic scale. Any given increase, regardless of its absolute size, is related to a given base quantity. Thus, a perfectly straight line on such a graph denotes a constant percentage rate of increase, and not a constant absolute increase. It is the slope of the line or curve which is significant in such a graph. The steeper the slope, whether it be downwards or upwards, the more marked is the rate of change." (Alfred R Ilersic, "Statistics", 1959)

"This type of graph possesses a number of advantages. It is possible to graph a number of series of widely differing magnitudes on a single chart and bring out any relationship between their movements. How- ever wide the amplitude of the fluctuations in the series, a logarithmic scale reduces them to manageable size on a single sheet of graph paper, whereas, on a normal scale, it might prove impossible to get the larger fluctuations on to a single chart, except by so reducing the scale that all the other smaller movements in the series are almost obliterated." (Alfred R Ilersic, "Statistics", 1959)

"Time series analysis often requires more knowledge of the data and relevant information about their background than it does of statistical techniques. Whereas the data in some other fields may be controlled so as to increase their representativeness, economic data are so changeable in their nature that it is usually impossible to sort out the separate effects of the various influences. Attempts to isolate cyclical, seasonal and irregular, or random movements, are made primarily in the hope that some underlying pattern of change over time may be revealed."  (Alfred R Ilersic, "Statistics", 1959)

"When using estimated figures, i.e. figures subject to error, for further calculation make allowance for the absolute and relative errors. Above all, avoid what is known to statisticians as 'spurious' accuracy. For example, if the arithmetic Mean has to be derived from a distribution of ages given to the nearest year, do not give the answer to several places of decimals. Such an answer would imply a degree of accuracy in the results of your calculations which are quite un- justified by the data. The same holds true when calculating percentages." (Alfred R Ilersic, "Statistics", 1959)

"While it is true to assert that much statistical work involves arithmetic and mathematics, it would be quite untrue to suggest that the main source of errors in statistics and their use is due to inaccurate calculations." (Alfred R Ilersic, "Statistics", 1959)

On Hypotheses: The Riemann Hypothesis

"Whoever proves or disproves [the Riemann Hypothesis] will cover himself in glory..." (Eric T Bell, 1937)

"[...] the Riemann hypothesis remains one of the outstanding challenges of mathematics, a prize which has tantalized and eluded some of the most brilliant mathematicians of this century...Hilbert is reputed to have said that the first comment he would make after waking at the end of a thousand year sleep would be, 'Is the Riemann hypothesis established yet?'" (Richard E  Bellman, A Brief Introduction of Theta Functions, 1961)

"At this point, it is not possible to remain silent on what is probably the most intriguing unsolved problem in the theory of the zeta function and actually in all of number theory - and most likely even one of the most important unsolved problems in contemporary mathematics, namely the famous Riemann hypothesis. [...] Still, the problem is open and fascinates and teases the best contemporary minds." (Emil Grosswald, "Topics in the Theory of Numbers", 1966)

"The failure of the Riemann hypothesis would create havoc in the distribution of prime numbers. This fact alone singles out the Riemann hypothesis as the main open question of prime number theory." (Enrico Bombieri,  "Prime Territory", The Sciences,  1992)

"The Riemann hypothesis [...] is still widely considered to be one of the greatest unsolved problems in mathematics, sure to wreath its conqueror with glory." (Bruce Schechter, "143-year-old problem still has mathematicians guessing", 2002)

"The dependence of so many results on Riemann's challenge is why mathematicians refer to it as a hypothesis rather than a conjecture. The word 'hypothesis' has the much stronger connotation of a necessary assumption that a mathematician makes in order to build a theory. 'Conjecture', in contrast, represents simply a prediction of how mathematicians believe their world behaves. Many have had to accept their inability to solve Riemann's riddle and have simply adopted his prediction as a working hypothesis. If someone can turn the hypothesis into a theorem, all those unproven results would be validated." (Marcus du Sautoy, "The Music of the Primes", 2003)

"The result has caught the imagination of most mathematicians because it is so unexpected, connecting two seemingly unrelated areas in mathematics; namely, number theory, which is the study of the discrete, and complex analysis, which deals with continuous processes." (David M Burton, "Elementary Number Theory", 2006)

"Just as music is not about reaching the final chord, mathematics is about more than just the result. It is the journey that excites the mathematician. I read and reread proofs in much the same way as I listen to a piece of music: understanding how themes are established, mutated, interwoven and transformed. What people don't realise about mathematics is that it involves a lot of choice: not about what is true or false (I can't make the Riemann hypothesis false if it's true), but from deciding what piece of mathematics is worth ‘listening to’." (Marcus du Sautoy, "Listen by numbers: music and maths", 2011)

"If [the Riemann Hypothesis is] not true, then the world is a very different place. The whole structure of integers and prime numbers would be very different to what we could imagine. In a way, it would be more interesting if it were false, but it would be a disaster because we've built so much round assuming its truth." (P  Sarnak)

"The Riemann Hypothesis is a precise statement, and in one sense what it means is clear, but what it's connected with, what it implies, where it comes from, can be very unobvious." (M Huxley)

"[...] the Riemann Hypothesis will be settled without any fundamental changes in our mathematical thoughts, namely, all tools are ready to attack it but just a penetrating idea is missing." (Y Motohashi)

"The consequences [of the Riemann Hypothesis] are fantastic: the distribution of primes, these elementary objects of arithmetic. And to have tools to study the distribution of these of objects." (H Iwaniec)

On Arithmetic (Unsourced)

"Arithmetic, then, means dealing logically with certain facts that we know, about numbers, with a view to arriving at knowledge which as yet we do not possess." (Philosophy & Fun of Algebra)

"As arithmetic and algebra are sciences of great clearness, certainty, and extent, which are immediately conversant about signs, upon the skillful use whereof they entirely depend, so a little attention to them may possibly help us to judge of the progress of the mind in other sciences, which, though differing in nature, design, and object, may yet agree in the general methods of proof and inquiry." (George Berkeley)

"I compare arithmetic with a tree that unfolds upwards in a multitude of techniques and theorems while the root drives into the depths." (F L Gottlob Frege)

"Music is the arithmetic of sounds as optics is the geometry of light." (Claude Debussy)

"Music is the hidden arithmetical exercise of a soul unconscious that it is calculating." (Gottfried W Leibniz)

"The human mind has never invented a labor-saving machine equal to algebra." (J Willard Gibbs)

"The mathematical phenomenon always develops out of simple arithmetic, so useful in everyday life, out of numbers, those weapons of the gods; the gods are there, behind the wall, at play with numbers." (Le Corbusier)

"The pleasure we obtain from music comes from counting, but counting unconsciously. Music is nothing but unconscious arithmetic." (Gottfried W Leibniz)

"You cannot ask us to take sides against arithmetic." (Winston S Churchill)