16 November 2024

On Hypothesis Testing III

 "A little thought reveals a fact widely understood among statisticians: The null hypothesis, taken literally (and that’s the only way you can take it in formal hypothesis testing), is always false in the real world. [...] If it is false, even to a tiny degree, it must be the case that a large enough sample will produce a significant result and lead to its rejection. So if the null hypothesis is always false, what’s the big deal about rejecting it?" (Jacob Cohen, "Things I Have Learned (So Far)", American Psychologist, 1990)

"I believe [...] that hypothesis testing has been greatly overemphasized in psychology and in the other disciplines that use it. It has diverted our attention from crucial issues. Mesmerized by a single all-purpose, mechanized, ‘objective’ ritual in which we convert numbers into other numbers and get a yes-no answer, we have come to neglect close scrutiny of where the numbers come from." (Jacob Cohen, "Things I have learned (so far)", American Psychologist 45, 1990)

"Despite the stranglehold that hypothesis testing has on experimental psychology, I find it difficult to imagine a less insightful means of transitting from data to conclusions." (Geoffrey R Loftus, "On the tyranny of hypothesis testing in the social sciences", Contemporary Psychology 36, 1991)

"How has the virtually barren technique of hypothesis testing come to assume such importance in the process by which we arrive at our conclusions from our data?" (Geoffrey R Loftus, "On the tyranny of hypothesis testing in the social sciences", Contemporary Psychology 36, 1991)

"This remarkable state of affairs [overuse of significance testing] is analogous to engineers’ teaching (and believing) that light consists only of waves while ignoring its particle characteristics - and losing in the process, of course, any motivation to pursue the most interesting puzzles and paradoxes in the field." (Geoffrey R Loftus, "On the tyranny of hypothesis testing in the social sciences", Contemporary Psychology 36, 1991)

"Whereas hypothesis testing emphasizes a very narrow question (‘Do the population means fail to conform to a specific pattern?’), the use of confidence intervals emphasizes a much broader question (‘What are the population means?’). Knowing what the means are, of course, implies knowing whether they fail to conform to a specific pattern, although the reverse is not true. In this sense, use of confidence intervals subsumes the process of hypothesis testing." (Geoffrey R Loftus, "On the tyranny of hypothesis testing in the social sciences", Contemporary Psychology 36, 1991)

"After four decades of severe criticism, the ritual of null hypothesis significance testing - mechanical dichotomous decisions around a sacred .05 criterion - still persist. This article reviews the problems with this practice [...] What’s wrong with [null hypothesis significance testing]? Well, among many other things, it does not tell us what we want to know, and we so much want to know what we want to know that, out of desperation, we nevertheless believe that it does!" (Jacob Cohen, "The earth is round (p<.05)", American Psychologist 49, 1994)

"I argued that hypothesis testing is fundamentally inappropriate for ecological risk assessment, that its use has undesirable consequences for environmental protection, and that preferable alternatives exist for statistical analysis of data in ecological risk assessment. The conclusion of this paper is that ecological risk assessors should estimate risks rather than test hypothesis" (Glenn W Suter, "Abuse of hypothesis testing statistics in ecological risk assessment", Human and Ecological Risk Assessment 2, 1996)

"I contend that the general acceptance of statistical hypothesis testing is one of the most unfortunate aspects of 20th century applied science. Tests for the identity of population distributions, for equality of treatment means, for presence of interactions, for the nullity of a correlation coefficient, and so on, have been responsible for much bad science, much lazy science, and much silly science. A good scientist can manage with, and will not be misled by, parameter estimates and their associated standard errors or confidence limits." (Marks Nester, "A Myopic View and History of Hypothesis Testing", 1996)

"Statistical hypothesis testing is commonly used inappropriately to analyze data, determine causality, and make decisions about significance in ecological risk assessment,[...] It discourages good toxicity testing and field studies, it provides less protection to ecosystems or their components that are difficult to sample or replicate, and it provides less protection when more treatments or responses are used. It provides a poor basis for decision-making because it does not generate a conclusion of no effect, it does not indicate the nature or magnitude of effects, it does address effects at untested exposure levels, and it confounds effects and uncertainty[...]. Risk assessors should focus on analyzing the relationship between exposure and effects[...]."  (Glenn W Suter, "Abuse of hypothesis testing statistics in ecological risk assessment", Human and Ecological Risk Assessment 2, 1996)

On Hypothesis Testing II

"Small wonder that students have trouble [with statistical hypothesis testing]. They may be trying to think." (W Edwards Deming, "On probability as a basis for action", American Statistician 29, 1975)

"Tests appear to many users to be a simple way to discharge the obligation to provide some statistical treatment of the data." (H V Roberts, "For what use are tests of hypotheses and tests of significance",  Communications in Statistics [Series A], 1976)

"In practice, of course, tests of significance are not taken seriously." (Louis Guttman, "The illogic of statistical inference for cumulative science", Applied Stochastic Models and Data Analysis, 1985)

"Most readers of The American Statistician will recognize the limited value of hypothesis testing in the science of statistics. I am not sure that they all realize the extent to which it has become the primary tool in the religion of Statistics." (David Salsburg, The Religion of Statistics as Practiced in Medical Journals, "The American Statistician" 39, 1985)

"Since a point hypothesis is not to be expected in practice to be exactly true, but only approximate, a proper test of significance should almost always show significance for large enough samples. So the whole game of testing point hypotheses, power analysis notwithstanding, is but a mathematical game without empirical importance." (Louis Guttman, "The illogic of statistical inference for cumulative science", Applied Stochastic Models and Data Analysis, 1985

"We shall marshal arguments against [significance] testing, leading to the conclusion that it be abandoned by all substantive science and not just by educational research and other social sciences which have begun to raise voices against the virtual tyranny of this branch of inference in the academic world." (Louis Guttman, "The illogic of statistical inference for cumulative science", Applied Stochastic Models and Data Analysis, 1985)

"Analysis of variance [...] stems from a hypothesis-testing formulation that is difficult to take seriously and would be of limited value for making final conclusions." (Herman Chernoff, Comment,  The American Statistician 40(1), 1986)

"We are better off abandoning the use of hypothesis tests entirely and concentrating on developing continuous measures of toxicity which can be used for estimation." (David Salsburg, "Statistics for Toxicologists", 1986)

"Beware of the problem of testing too many hypotheses; the more you torture the data, the more likely they are to confess, but confessions obtained under duress may not be admissible in the court of scientific opinion." (Stephen M Stigler, "Neutral Models in Biology", 1987)

On Hypothesis Testing I

"Statistics is the fundamental and most important part of inductive logic. It is both an art and a science, and it deals with the collection, the tabulation, the analysis and interpretation of quantitative and qualitative measurements. It is concerned with the classifying and determining of actual attributes as well as the making of estimates and the testing of various hypotheses by which probable, or expected, values are obtained. It is one of the means of carrying on scientific research in order to ascertain the laws of behavior of things - be they animate or inanimate. Statistics is the technique of the Scientific Method." (Bruce D Greenschields & Frank M Weida, "Statistics with Applications to Highway Traffic Analyses", 1952)

"The peculiarity of [...] statistical hypotheses is that they are not conclusively refutable by any experience." (Richard B Braithwaite, "Scientific Explanation: A Study of the Function of Theory, Probability and Law in Science", 1953)

"Tests of the null hypothesis that there is no difference between certain treatments are often made in the analysis of agricultural or industrial experiments in which alternative methods or processes are compared. Such tests are [...] totally irrelevant. What are needed are estimates of magnitudes of effects, with standard errors." (Francis J Anscombe, "Discussion on Dr. David’s and Dr. Johnson’s Paper", Journal of the Royal Statistical Society B 18, 1956)

"[...] the tests of null hypotheses of zero differences, of no relationships, are frequently weak, perhaps trivial statements of the researcher’s aims [...] in many cases, instead of the tests of significance it would be more to the point to measure the magnitudes of the relationships, attaching proper statements of their sampling variation. The magnitudes of relationships cannot be measured in terms of levels of significance." (Leslie Kish, "Some statistical problems in research design", American Sociological Review 24, 1959)

"In view of our long-term strategy of improving our theories, our statistical tactics can be greatly improved by shifting emphasis away from over-all hypothesis testing in the direction of statistical estimation. This always holds true when we are concerned with the actual size of one or more differences rather than simply in the existence of differences." (David A Grant, "Testing the null hypothesis and the strategy and tactics of investigating theoretical models", Psychological Review 69, 1962)

"[...] we need to get on with the business of generating [...] hypotheses and proceed to do investigations and make inferences which bear on them, instead of [...] testing the statistical null hypothesis in any number of contexts in which we have every reason to suppose that it is false in the first place." (David Bakan, "The test of significance in psychological research", Psychological Bulletin 66, 1966)

"All testing, all confirmation and disconfirmation of a hypothesis takes place already within a system. And this system is not a more or less arbitrary and doubtful point of departure for all our arguments; no it belongs to the essence of what we call an argument. The system is not so much the point of departure, as the element in which our arguments have their life." (Ludwig Wittgenstein, "On Certainty", 1969)

"Science consists simply of the formulation and testing of hypotheses based on observational evidence; experiments are important where applicable, but their function is merely to simplify observation by imposing controlled conditions." (Henry L Batten, "Evolution of the Earth", 1971)

"[...] the statistical power of many psychological studies is ridiculously low. This is a self-defeating practice: it makes for frustrated scientists and inefficient research. The investigator who tests a valid hypothesis but fails to obtain significant results cannot help but regard nature as untrustworthy or even hostile." (Amos Tversky & Daniel Kahneman, "Belief in the law of small numbers", Psychological Bulletin 76(2), 1971) 

"Decision-making problems (hypothesis testing) involve situations where it is desired to make a choice among various alternative decisions (hypotheses). Such problems can be viewed as generalized state estimation problems where the definition of state has simply been expanded." (Fred C Scweppe, "Uncertain dynamic systems", 1973)

"Hypothesis testing can introduce the need for multiple models for the multiple hypotheses and,' if appropriate, a priori probabilities. The one modeling aspect of hypothesis testing that has no estimation counterpart is the problem of specifying the hypotheses to be considered. Often this is a critical step which influences both performance arid the difficulty of implementation." (Fred C Scweppe, "Uncertain dynamic systems", 1973)

"Pattern recognition can be viewed as a special case of hypothesis testing. In pattern recognition, an observation z is to be used to decide what pattern caused it. Each possible pattern can be viewed as one hypothesis. The main problem in pattern recognition is the development of models for the z corresponding to each pattern (hypothesis)." (Fred C Scweppe, "Uncertain dynamic systems", 1973)

"The term hypothesis testing arises because the choice as to which process is observed is based on hypothesized models. Thus hypothesis testing could also be called model testing. Hypothesis testing is sometimes called decision theory. The detection theory of communication theory is a special case." (Fred C Scweppe, "Uncertain dynamic systems", 1973)

09 November 2024

Douglas T Ross - Collected Quotes

"Automatic design has the computer do too much and the human do too little, whereas automatic programming has the human do too much and the computer do too little. Both techniques are important, but are not representative for what we wish to mean by computer-aided design." (Douglas T Ross, "Computer-Aided Design: A Statement of Objectives", 1960)

"Computer-aided design is not automatic design, although it must include many automatic design features. By automatic design we mean design procedures which are capable of being completely specified in a form which a computer can execute without human intervention." (Douglas T Ross, "Computer-Aided Design: A Statement of Objectives", 1960)

"It is very difficult to define what is meant by computer-aided design since the complete definition is, in fact, the sum and substance of the total project effort which has only begun. It is much easier to describe, what is not computer-aided design as we mean it." (Douglas T Ross, "Computer-Aided Design: A Statement of Objectives", 1960)

"The objective of the Computer-Aided Design Project is to evolve a machine systems which will permit the human designer and the computer to work together on creative design problems."  (Douglas T Ross, "Computer-Aided Design: A Statement of Objectives", 1960)

"Mechanical drawings and blueprints are not mere pictures, but a complete and rich language. In blueprint language, scientific, mathematical, and geometric formulations, notations, mensurations, and naming do not merely describe an object or process, they actually model it. Because of broad differences in subject, purpose, roles, and the needs of the people who use them, many forms of blueprint have evolved, but all rigorously present well structured information in understandable form." (Douglas T Ross, "Structured analysis (SA): A language for communicating ideas", IEEE Transactions on Software Engineering Vol. 3 No. 1, 1977)

"Structured analysis (SA) combines blueprint-like graphic language with the nouns and verbs of any other language to provide a hierarchic, top-down, gradual exposition of detail in the form of an SA model. The things and happenings of a subject are expressed in a data decomposition and an activity decomposition, both of which employ the same graphic building block, the SA box, to represent a part of a whole. SA arrows, representing input, output, control, and mechanism, express the relation of each part to the whole." (Douglas T Ross, "Structured analysis (SA): A language for communicating ideas", IEEE Transactions on Software Engineering Vol. 3 No. 1, 1977)

"The natural law of good communications takes the following, quite different, form in SA: Everything worth saying about anything worth saying something about must be expressed in six or fewer pieces." (Douglas T Ross, "Structured analysis (SA): A language for communicating ideas", IEEE Transactions on Software Engineering Vol. 3 No. 1, 1977)

"There are certain basic, known principles about how people's minds go about the business of understanding, and communicating understanding by means of language, which have been known and used for many centuries. No matter how these principles are addressed, they always end up with hierarchic decomposition as being the heart of good storytelling." (Douglas T Ross, "Structured analysis (SA): A language for communicating ideas", IEEE Transactions on Software Engineering Vol. 3 No. 1, 1977)

"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 No. 1, 1977)

"A general theme for what I'm trying to convey and what actually drove me and my very industrious and creative project members over all these years, is… that there is much more to it than pictures. It has to be a picture language. There has to be meaning there, and the meaning is useful. You're trying to solve problems. So it really comes down to man machine problem solving. Better means of communication and expression is what always has driven our work." (Douglas T Ross, "Retrospectives: The Early Years in Computer Graphics at at MIT", Lincoln Lab and Harvard, 1989)

"There is a rigorous science, just waiting to be recognized and developed, which encompasses the whole of 'the software problem,' as defined, including the hardware, software, languages, devices, logic, data, knowledge, users, users, and effectiveness, etc. for end-users, providers, enablers, commissioners, and sponsors, alike." (Douglas T Ross,1989)

08 November 2024

George B Dyson - Collected Quotes

"An Internet search engine is a finite-state, deterministic machine, except at those junctures where people, individually and collectively, make a nondeterministic choice as to which results are selected as meaningful and given a click. These clicks are then immediately incorporated into the state of the deterministic machine, which grows ever so incrementally more knowledgeable with every click. This is what Turing defined as an oracle machine."  (George B Dyson, "Turing's Cathedral: The Origins of the Digital Universe", 2012)

"If life, by some chance, happens to have originated, and survived, elsewhere in the universe, it will have had time to explore an unfathomable diversity of forms. Those best able to survive the passage of time, adapt to changing environments, and migrate across interstellar distances will become the most widespread. A life form that assumes digital representation, for all or part of its life cycle, will be able to travel at the speed of light." (George B Dyson, "Turing's Cathedral: The Origins of the Digital Universe", 2012)

"In our universe, we measure time with clocks, and computers have a 'clock speed', but the clocks that govern the digital universe are very different from the clocks that govern ours. In the digital universe, clocks exist to synchronize the translation between bits that are stored in memory (as structures in space) and bits that are communicated by code (as sequences in time). They are clocks more in the sense of regulating escapement than in the sense of measuring time."(George B Dyson, "Turing's Cathedral: The Origins of the Digital Universe", 2012)

"It is characteristic of objects of low complexity that it is easier to talk about the object than produce it and easier to predict its properties than to build it." (George B Dyson, "Turing's Cathedral: The Origins of the Digital Universe", 2012)

"Sixty-some years ago, biochemical organisms began to assemble digital computers. Now digital computers are beginning to assemble biochemical organisms. Viewed from a distance, this looks like part of a life cycle. But which part? Are biochemical organisms the larval phase of digital computers? Or are digital computers the larval phase of biochemical organisms?" (George B Dyson, "Turing's Cathedral: The Origins of the Digital Universe", 2012)

"Life evolved, so far, by making use of the viral cloud as a source of backup copies and a way to rapidly exchange genetic code. Life may be better adapted to the digital universe than we think." (George B Dyson, "Turing's Cathedral: The Origins of the Digital Universe", 2012)

"Mathematical reasoning may be regarded rather schematically as the exercise of a combination of two faculties, which we may call intuition and ingenuity [...] (George B Dyson, "Turing's Cathedral: The Origins of the Digital Universe", 2012)

"Monte Carlo is able to discover practical solutions to otherwise intractable problems because the most efficient search of an unmapped territory takes the form of a random walk. Today’s search engines, long descended from their ENIAC-era ancestors, still bear the imprint of their Monte Carlo origins: random search paths being accounted for, statistically, to accumulate increasingly accurate results. The genius of Monte Carlo - and its search-engine descendants - lies in the ability to extract meaningful solutions, in the face of overwhelming information, by recognizing that meaning resides less in the data at the end points and more in the intervening paths." (George B Dyson, "Turing's Cathedral: The Origins of the Digital Universe", 2012)

"Music allows us to assemble temporal sequences into mental scaffolding that transcends the thinness of time in which we live." (George B Dyson, "Turing's Cathedral: The Origins of the Digital Universe", 2012)

"One of the facets of extreme originality is not to regard as obvious the things that lesser minds call obvious," (George B Dyson, "Turing's Cathedral: The Origins of the Digital Universe", 2012)

"Over long distances, it is expensive to transport structures, and inexpensive to transmit sequences. Turing machines, which by definition are structures that can be encoded as sequences, are already propagating themselves, locally, at the speed of light. The notion that one particular computer resides in one particular location at one time is obsolete. (George Dyson, "Turing's Cathedral: The Origins of the Digital Universe", 2012) 

"Random search can be more efficient than nonrandom search - something that Good and Turing had discovered at Bletchley Park. A random network, whether of neurons, computers, words, or ideas, contains solutions, waiting to be discovered, to problems that need not be explicitly defined." (George B Dyson, "Turing's Cathedral: The Origins of the Digital Universe", 2012)

"The brain is a statistical, probabilistic system, with logic and mathematics running as higher-level processes. The computer is a logical, mathematical system, upon which higher-level statistical, probabilistic systems, such as human language and intelligence, could possibly be built." (George B Dyson, "Turing's Cathedral: The Origins of the Digital Universe", 2012)

"The good news is that, as Leibniz suggested, we appear to live in the best of all possible worlds, where the computable functions make life predictable enough to be survivable, while the noncomputable functions make life (and mathematical truth) unpredictable enough to remain interesting, no matter how far computers continue to advance."  (George B Dyson, "Turing's Cathedral: The Origins of the Digital Universe", 2012)

"The fundamental, indivisible unit of information is the bit. The fundamental, indivisible unit of digital computation is the transformation of a bit between its two possible forms of existence: as structure (memory) or as sequence (code). This is what a Turing Machine does when reading a mark (or the absence of a mark) on a square of tape, changing its state of mind accordingly, and making (or erasing) a mark somewhere else." (George B Dyson, "Turing's Cathedral: The Origins of the Digital Universe", 2012)

"The genius of Monte Carlo - and its search-engine descendants - lies in the ability to extract meaningful solutions, in the face of overwhelming information, by recognizing that meaning resides less in the data at the end points and more in the intervening paths." (George B Dyson, "Turing's Cathedral: The Origins of the Digital Universe", 2012)

"The paradox of artificial intelligence is that any system simple enough to be understandable is not complicated enough to behave intelligently, and any system complicated enough to behave intelligently is not simple enough to understand. The path to artificial intelligence, suggested Turing, is to construct a machine with the curiosity of a child, and let intelligence evolve." (George B Dyson, "Turing's Cathedral: The Origins of the Digital Universe", 2012)

"The question of whether something is feasible in a type belongs to a higher logical type. It is characteristic of objects of low complexity that it is easier to talk about the object than produce it and easier to predict its properties than to build it. But in the complicated parts of formal logic it is always one order of magnitude harder to tell what an object can do than to produce the object." (George B Dyson, "Turing's Cathedral: The Origins of the Digital Universe", 2012)

"There are two kinds of creation myths: those where life arises out of the mud, and those where life falls from the sky. In this creation myth, computers arose from the mud, and code fell from the sky." (George B Dyson, "Turing's Cathedral: The Origins of the Digital Universe", 2012)

"Where does meaning come in? If everything is assigned a number, does this diminish the meaning in the world? What Gödel (and Turing) proved is that formal systems will, sooner or later, produce meaningful statements whose truth can be proved only outside the system itself. This limitation does not confine us to a world with any less meaning. It proves, on the contrary, that we live in a world where higher meaning exists." (George B Dyson, "Turing's Cathedral: The Origins of the Digital Universe", 2012)

"Nature uses digital computing for generation-to-generation information storage, combinatorics, and error correction but relies on analog computing for real-time intelligence and control." (George B Dyson, Analogia: The Emergence of Technology Beyond Programmable Control", 2020)

03 November 2024

A Picture's Worth

"The drawing shows me at a glance what would be spread over ten pages in a book." (Ivan Turgenev, 1862) [2]

"Sometimes, half a dozen figures will reveal, as with a lighting-flash, the importance of a subject which ten thousand labored words with the same purpose in view, had left at last but dim and uncertain." (Mark Twain, "Life on the Mississippi", 1883) 

"One good picture is worth many pages of written description." (William Sproston Caine, 1891) [2]

"One look is worth a thousand words" (Kathleen Caffyn, 1903) 

"Use a picture. It's worth a thousand words." (Arthur Brisbane, The Post-Standard, 1911)

"One Look Is Worth A Thousand Words" ([advertisement] 1913)

"A picture is worth ten thousand words. If you can’t see the truth in these pictures you are among the vast majority that must learn only by experience." (Arthur Brisbane, 1915)

"One picture is worth ten thousand words." (Frederick R Barnard, Printer’s Ink, 1921)

"One Picture Worth Ten Thousand Words" ([Chinese proverb] 1927)

"In many instances, a picture is indeed worth a thousand words. To make this true in more diverse circumstances, much more creative effort is needed to pictorialize the output from data analysis. Naive pictures are often extremely helpful, but more sophisticated pictures can be both simple and even more informative." (John W Tukey & Martin B Wilk, "Data Analysis and Statistics: An Expository Overview", 1966)

"One word is worth a thousand pictures. If it's the right word." (Edward Abbey, "Beyond the Wall: Essays from the Outside", 1984)

"A picture may be worth a thousand words, a formula is worth a thousand pictures." (Edsger Dijkstra, [conference at ETH Zurich] 1994)

"A magnificent picture is never worth a thousand perfect words." (John Dunning, "The Bookman's Wake", 1995)

"A picture tells a thousand words. But you get a thousand pictures from someone's voice." (Paul Fleischman, "Seek", 2001)

"If a picture is worth a thousand words, a metaphor is worth a thousand pictures." (Daniel H Pink, "A Whole New Mind: Why Right-Brainers Will Rule the Future", 2005)

"A picture may be worth a thousand words, but not all pictures are readable, interpretable, meaningful, or relevant." (Kristen Sosulski, "Data Visualization Made Simple: Insights into Becoming Visual", 2018)

"A good metaphor is worth a thousand pictures." (Anon) 

"As the Chinese say, 1001 words is worth more than a picture." (John McCarthy [source]) 

References:
[1] Wikipedia (2024) A picture is worth a thousand words [link]
[2] Quote Investigator (2022) A Picture Is Worth Ten Thousand Words [link
[3] SQL-Troubles (2024) Charts vs. Thousand Words [link]

29 October 2024

David G Green - Collected Quotes

"Although it might be intuitively apparent that a system is complex, defining complexity has proved difficult to pin down with numerous definitions on record. As yet there is no agreed theory of complexity. Much of the mathematics is intractable and computer simulation plays a major part." (Terry R J Bossomaier & David G Green, 2000) 

"Although many natural phenomena may result from the interaction of complex entities, the details of the components may be unimportant. In the discussion of neural networks, the individual neuron turns out to be a highly sophisticated biological system. But the collective properties of neurons may be captured by spin-glass models, in which the neuron is simplified to a binary quantity […] " (Terry R J Bossomaier & David G Green, 2000) 

"Interaction: the other major source of complexity is the interaction of many autonomous, adaptive agents. Again, there are many questions to ask about the agents, the nature of the interaction and the circumstances in which complex surface phenomena result. (Terry R J Bossomaier & David G. Green, 2000)

"Iteration: fractals and chaos result from repetition of simple operations. These generating rules produce complex phenomena. There are many interesting questions to ask about how to describe the processes, how to measure the resulting complexity, whether we can work backwards from the reult to the rules and so on. (Terry R J Bossomaier & David G. Green, 2000)

"Of course what we would all like to see is a general theory of complex systems or complexity. Despite several promising candidates the selection process is still under way. Maybe there is no universal theory, but there are certainly common paradigms and methods which have proved to be useful across a wide area." (Terry R J Bossomaier & David G Green, 2000) 

The evident power of simple heuristics […] teaches us the important lesson that global behavior patterns, and social organization, can emerge out of local interactions. Organisms do not necessarily need to have an over-riding plan nor do they require awareness of the large-scale. Grand patterns and processes can emerge as the nett effect of small-scale, local behavior.

"If entropy must increase, then how is it possible (say) for all the variety of the living world to persist? The usual answer to the above question is that living systems are open systems, not closed, so the law does not apply locally. However this answer is somewhat unsatisfying. In effect all systems are open systems, since everything interacts with its surroundings to some degree." (David G Green, 2000) 

"The really crucial question in multi-object systems is whether local interactions do grow into large-scale patterns." (David G Green, 2000) 

"The self-similarity on different scales arises because growth often involves iteration of simple, discrete processes (e.g. branching). These repetitive processes can often be summarized as sets of simple rules." (David G Green, 2000) 

27 October 2024

Paul Klee - Collected Quotes

"Our initial perplexity before nature is explained by our seeing at first the small outer branches and not penetrating to the main branches or the trunk. But once this is realized, one will perceive a repetition of the whole law even in the outermost leaf and turn it to good use." (Paul Klee, [diary entry] 1904)

"When looking at any significant work of art, remember that a more significant one probably has had to be sacrificed." (Paul Klee, [diary entry] 1904)

"The beautiful, which is perhaps inseparable from art, is not after all tied to the subject, but to the pictorial representation. In this way and in no other does art overcome the ugly without avoiding it." (Paul Klee, [diary entry] 1905)

"Things are not quite so simple with 'pure' art as it is dogmatically claimed. In the final analysis, a drawing simply is no longer a drawing, no matter how self-sufficient its execution may be. It is a symbol, and the more profoundly the imaginary lines of projection meet higher dimensions, the better. In this sense I shall never be a pure artist as the dogma defines him. We higher creatures are also mechanically produced children of God, and yet intellect and soul operate within us in completely different dimensions." (Paul Klee, [diary entry] 1905)

"Nature can afford to be prodigal in everything, the artist must be frugal down to the last detail."  Paul Klee, [diary entry] 1909)

"First of all, the art of living; then as my ideal profession, poetry and philosophy, and as my real profession, plastic arts; in the last resort, for lack of income, illustrations." (Paul Klee, cca. 1910

"Graphic work as the expressive movement of the hand holding the recording pencil.... is so fundamentally different from dealing with tone and color that one can use this technique quite well in the dark, even in the blackest night. On the other hand, tone (movement from light to dark) presupposes some light, and color presupposes a great deal of light." (Paul Klee, 1912)

"We document, explain, justify, construct, organize: these are good things, but we do not succeed in coming to the whole [...]. But we may as well calm down: construction is not absolute. Our virtue is this: by cultivating the exact we have laid the foundations for a science of art, including the unknown X." (Paul Klee, "Statement of 1917"

"A tendency toward the abstract is inherent in linear expression: graphic imagery being confined to outlines has a fairy-like quality and at the same time can achieve great precision." (Paul Klee, "Creative Credo", 1920)

"Things appear to assume a broader and more diversified meaning, often seemingly contradicting the rational experience of yesterday. There is a striving to emphasize the essential character of the accidental." (Paul Klee, "Creative Credo", 1920)

"For the artist communication with nature remains the most essential condition. The artist is human; himself nature; part of nature within natural space." (Paul Klee, 1923)

"It is possible that a picture will move far away from Nature and yet find its way back to reality. The faculty of memory, experience at a distance produces pictorial associations." (Paul Klee, cca. 1925)

"Thought is the medially between earth and world. The broader the magnitude of his reach, the more painful man's tragic limitation. Thought is the medially between earth and world. The broader the magnitude of his reach, the more painful man's tragic limitation. To get where motion is interminate." ( Paul Klee, "Pedagogical Sketch Book, 1925)

"The longer a line, the more of the time element it contains. Distance is time whereas a surface is apprehended more in terms of the moment." (Paul Klee, "Exact Experiments in the Realm of Art", 1927)

"What had already been done for music by the end of the eighteenth century has at last been begun for the pictorial arts. Mathematics and physics furnished the means in the form of rules to be followed and to be broken. In the beginning it is wholesome to be concerned with the functions and to disregard the finished form. Studies in algebra, in geometry, in mechanics characterize teaching directed towards the essential and the functional, in contrast to apparent. One learns to look behind the façade, to grasp the root of things. One learns to recognize the undercurrents, the antecedents of the visible. One learns to dig down, to uncover, to find the cause, to analyze." (Paul Klee, "Bauhaus prospectus", 1929)

"Art should be like a holiday: something to give a man the opportunity to see things differently and to change his point of view." (Paul Klee)

"It is interesting to observe how real the object remains, in spite of all abstractions." (Paul Klee)

26 October 2024

Richard B Braithwaite - Collected Quotes

"It has been a fortunate fact in the modern history of physical science that the scientist constructing a new theoretical system has nearly always found that the mathematics [...] required [...] had already been worked out by pure mathematicians for their own amusement [...] The moral for statesmen would seem to be that, for proper scientific 'planning' , pure mathematics should be endowed fifty years ahead of scientists." (Richard B Braithwaite, "Scientific Explanation: A Study of the Function of Theory, Probability and Law in Science", 1953)

"[...] no batch of observations, however large, either definitively rejects or definitively fails to reject the hypothesis H0." (Richard B Braithwaite, "Scientific Explanation: A Study of the Function of Theory, Probability and Law in Science", 1953)

"The peaks of science may appear to be floating in the clouds, but their foundations are in the hard facts of experience." (Richard B Braithwaite, "Scientific Explanation: A Study of the Function of Theory, Probability and Law in Science", 1953)

"The peculiarity of [...] statistical hypotheses is that they are not conclusively refutable by any experience." (Richard B Braithwaite, "Scientific Explanation: A Study of the Function of Theory, Probability and Law in Science", 1953)

"The ultimate justification for any scientific belief will depend upon the main purpose for which we think scientifically - that of predicting and thereby controlling the future." (Richard B Braithwaite, "Scientific Explanation: A Study of the Function of Theory, Probability and Law in Science", 1953)

"The world is not made up of empirical facts with the addition of the laws of nature: what we call the laws of nature are conceptual devices by which we organize our empirical knowledge and predict the future." (Richard B Braithwaite, "Scientific Explanation: A Study of the Function of Theory, Probability and Law in Science", 1953)





Howard Wainer - Collected Quotes

"Although arguments can be made that high data density does not imply that a graphic will be good, nor one with low density bad, it does reflect on the efficiency of the transmission of information. Obviously, if we hold clarity and accuracy constant, more information is better than less. One of the great assets of graphical techniques is that they can convey large amounts of information in a small space." (Howard Wainer, "How to Display Data Badly", The American Statistician Vol. 38(2), 1984) 

"The essence of a graphic display is that a set of numbers having both magnitudes and an order are represented by an appropriate visual metaphor - the magnitude and order of the metaphorical representation match the numbers. We can display data badly by ignoring or distorting this concept." (Howard Wainer, "How to Display Data Badly", The American Statistician Vol. 38(2), 1984)

"The standard error of most statistics is proportional to 1 over the square root of the sample size. God did this, and there is nothing we can do to change it." (Howard Wainer, "Improving Tabular Displays, With NAEP Tables as Examples and Inspirations", Journal of Educational and Behavioral Statistics Vol 22 (1), 1997)

"[…] a graph is nothing but a visual metaphor. To be truthful, it must correspond closely to the phenomena it depicts: longer bars or bigger pie slices must correspond to more, a rising line must correspond to an increasing amount. If a graphical depiction of data does not faithfully follow this principle, it is almost sure to be misleading. But the metaphoric attachment of a graphic goes farther than this. The character of the depiction ism a necessary and sufficient condition for the character of the data. When the data change, so too must their depiction; but when the depiction changes very little, we assume that the data, likewise, are relatively unchanging. If this convention is not followed, we are usually misled." (Howard Wainer, "Graphic Discovery: A trout in the milk and other visuals" 2nd, 2008)

"A graphic display has many purposes, but it achieves its highest value when it forces us to see what we were not expecting." (Howard Wainer, "Graphic Discovery: A trout in the milk and other visuals" 2nd, 2008)

"Nothing that had been produced before was even close. Even today, after more than two centuries of graphical experience, Playfair’s graphs remain exemplary standards for clearcommunication of quantitative phenomena. […] Graphical forms were available before Playfair, but they were rarely used to plot empirical information." (Howard Wainer, "Graphic Discovery: A trout in the milk and other visuals" 2nd, 2008)

"Oftentimes a statistical graphic provides the evidence for a plausible story, and the evidence, though perhaps only circumstantial, can be quite convincing. […] But such graphical arguments are not always valid. Knowledge of the underlying phenomena and additional facts may be required." (Howard Wainer, "Graphic Discovery: A trout in the milk and other visuals" 2nd, 2008)

"Placing a fact within a context increases its value greatly. […] . An efficacious way to add context to statistical facts is by embedding them in a graphic. Sometimes the most helpful context is geographical, and shaded maps come to mind as examples. Sometimes the most helpful context is temporal, and time-based line graphs are the obvious choice. But how much time? The ending date (today) is usually clear, but where do you start? The starting point determines the scale. […] The starting point and hence the scale are determined by the questions that we expect the graph to answer." (Howard Wainer, "Graphic Discovery: A trout in the milk and other visuals" 2nd, 2008)

"Simpson’s Paradox can occur whenever data are aggregated. If data are collapsed across a subclassification (such as grades, race, or age), the overall difference observed may not represent what is going on. Standardization can help correct this, but nothing short of random assignment of individuals to groups will prevent the possibility of yet another subclassificatiion, as yet unidentified, changing things around again. But I believe that knowing of the possibility helps us, so that we can contain the enthusiasm of our impulsive first inferences." (Howard Wainer, "Graphic Discovery: A trout in the milk and other visuals" 2nd, 2008)

"The appearance, and hence the perception, of any statistical graphic is massively influenced by the choice of scale. If the scale of the vertical axis is too narrow relative to the scale of the horizontal axis, random meanders look meaningful." (Howard Wainer, "Graphic Discovery: A trout in the milk and other visuals" 2nd, 2008)

"The difficult task of properly setting the scale of a graph remains difficult but not mysterious. There is agreement among experts spanning two hundred years. The default option should be to choose a scale that fills the plot with data. We can deviate from this under circumstances when it is better not to fill the plot with data, but those circumstances are usually clear. It is important to remember that the sin of using too small a scale is venial; the viewer can correct it. The sin of using too large a scale cannot be corrected without access to the original data; it can be mortal." (Howard Wainer, "Graphic Discovery: A trout in the milk and other visuals" 2nd, 2008)

"Usually the effectiveness of a good display increases with the complexity of the data. When there are only a few points, almost anything will do; even a pie chart with only three or four categories is usually comprehensible." (Howard Wainer, "Graphic Discovery: A trout in the milk and other visuals" 2nd, 2008)

"Thus when we look at, or prepare, a time-based statistical graphic, it is important to ask what is the right time scale, the right context, for the questions of greatest interest. The answer to this question is sometimes complex, but the very act of asking it provides us with some protection against surprises." (Howard Wainer, "Graphic Discovery: A trout in the milk and other visuals" 2nd, 2008)

"The only thing we know for sure about a missing data point is that it is not there, and there is nothing that the magic of statistics can do change that. The best that can be managed is to estimate the extent to which missing data have influenced the inferences we wish to draw." (Howard Wainer, "14 Conversations About Three Things", Journal of Educational and Behavioral Statistics Vol. 35(1, 2010)

"For an analyst to willfully avoid learning about the science is akin to malfeasance. Of course, it is likely that a deep understanding both of the science and of data analytic methods does not reside in the same person. When it does not, data analysis should be done jointly. It is my understanding that data mining is not often done as a team. This is unfortunate, for then it is too easy to miss what might have been found." (Howard Wainer, Comment, Journal of Computational and Graphical Statistics Vol. 20(1), 2011)

"Too often there is a disconnect between the people who run a study and those who do the data analysis. This is as predictable as it is unfortunate. If data are gathered with particular hypotheses in mind, too often they (the data) are passed on to someone who is tasked with testing those hypotheses and who has only marginal knowledge of the subject matter. Graphical displays, if prepared at all, are just summaries or tests of the assumptions underlying the tests being done. Broader displays, that have the potential of showing us things that we had not expected, are either not done at all, or their message is not able to be fully appreciated by the data analyst." (Howard Wainer, Comment, Journal of Computational and Graphical Statistics Vol. 20(1), 2011)


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