"The statistician who supposes that his main contribution to the planning of an experiment will involve statistical theory, finds repeatedly that he makes his most valuable contribution simply by persuading the investigator to explain why he wishes to do the experiment, by persuading him to justify the experimental treatments, and to explain why it is that the experiment, when completed, will assist him in his research." (Gertrude Cox, [lecture] 1951)
"When an engineer apologetically approaches a statistician, graph in hand, and asks how he should fit a straight line to these points, the situation is not unlike the moment when one’s daughter inquires where babies come from. There is a need for tact, there is a need for delicacy, but here is opportunity for enlightenment and it must not be discarded casually - or destroyed with the glib answer." (Forman S Acton, National Bureau of Standards Report, 1951)
"The fact is that, despite its mathematical base, statistics is as much an art as it is a science. A great many manipulations and even distortions are possible within the bounds of propriety. Often the statistician must choose among methods, a subjective process, and find the one that he will use to represent the facts."
"For that theory [mathematical theory of statistics] is solely concerned with working out the properties of the theoretical models, whereas what matters - and what in one sense is most difficult - is to decide what theoretical model best corresponds to the real world-situation to which statistical methods must be applied. There is a great danger that mathematical pupils will imagine that a knowledge of mathematical statistics alone makes a statistician." (David G Champemowne, "A Discussion on the Teaching of Mathematical Statistics at the University Level", Journal of the Royal Statistical Society Vol. 118, 1955)
"It is very easy to devise different tests which, on the average, have similar properties, [...] hey behave satisfactorily when the null hypothesis is true and have approximately the same power of detecting departures from that hypothesis. Two such tests may, however, give very different results when applied to a given set of data. The situation leads to a good deal of contention amongst statisticians and much discredit of the science of statistics. The appalling position can easily arise in which one can get any answer one wants if only one goes around to a large enough number of statisticians." (Frances Yates, "Discussion on the Paper by Dr. Box and Dr. Andersen", Journal of the Royal Statistical Society B Vol. 17, 1955)
"The mathematician, the statistician, and the philosopher do different things with a theory of probability. The mathematician develops its formal consequences, the statistician applies the work of the mathematician and the philosopher describes in general terms what this application consists in. The mathematician develops symbolic tools without worrying overmuch what the tools are for; the statistician uses them; the philosopher talks about them. Each does his job better if he knows something about the work of the other two." (Irving J Good, "Kinds of Probability", Science Vol. 129 (3347), 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)
"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)
"Years ago a statistician might have claimed that statistics deals with the processing of data [...]today’s statistician will be more likely to say that statistics is concerned with decision making in the face of uncertainty." (Herman Chernoff & Lincoln E Moses, "Elementary Decision Theory", 1959)
"One feature [...] which requires much more justification than is usually given, is the setting up of unplausible null hypotheses. For example, a statistician may set out a test to see whether two drugs have exactly the same effect, or whether a regression line is exactly straight. These hypotheses can scarcely be taken literally." (Cedric A B Smith, "Book review of Norman T. J. Bailey: Statistical Methods in Biology", Applied Statistics 9, 1960)
"Predictions, prophecies, and perhaps even guidance - those who suggested this title to me must have hoped for such-even though occasional indulgences in such actions by statisticians has undoubtedly contributed to the characterization of a statistician as a man who draws straight lines from insufficient data to foregone conclusions!" (John W Tukey, "Where do We Go From Here?", Journal of the American Statistical Association, Vol. 55 (289), 1960)
"A random sequence is a vague notion embodying the idea of a sequence in which each term is unpredictable to the uninitiated and whose digits pass a certain number of tests traditional with statisticians and depending somewhat on the uses to which the sequence is to be put." (Derrick H Lehmer, 1951)
"[...] 'statistics are only for the statistician', and even then, I might add, only for the good statistician." (Ely Devons, "Essays in Economics", 1961)
"[Statistics] is concerned with things we can count. In so far as things, persons, are unique or ill-defined, statistics are meaningless and statisticians silenced; in so far as things are similar and definite - so many workers over 25, so many nuts and bolts made during December - they can be counted and new statistical facts are born." (Maurice S Bartlett, "Essays on Probability and Statistics", 1962)
"The most important maxim for data analysis to heed, and one which many statisticians seem to have shunned is this: ‘Far better an approximate answer to the right question, which is often vague, than an exact answer to the wrong question, which can always be made precise.’ Data analysis must progress by approximate answers, at best, since its knowledge of what the problem really is will at best be approximate." (John W Tukey, "The Future of Data Analysis", Annals of Mathematical Statistics, Vol. 33, No. 1, 1962)
"Mathematical statistics provides an exceptionally clear example of the relationship between mathematics and the external world. The external world provides the experimentally measured distribution curve; mathematics provides the equation (the mathematical model) that corresponds to the empirical curve. The statistician may be guided by a thought experiment in finding the corresponding equation." (Marshall J Walker, "The Nature of Scientific Thought", 1963)
"Evaluation of the statistical reliability of a set of results is not mere calculation of standard errors and confidence limits. The statistician must go far beyond the statistical methods in textbooks. He must evaluate uncertainty in terms of possible uses of the data. Some of this writing is not statistical but draws on assistance from the expert in the subject-matter." (W Edwards Deming, "Principles of Professional Statistical Practice", Annals of Mathematical Statistics, 36(6), 1965)
"The statistician has no magic touch by which he may come in at the stage of tabulation and make something of nothing. Neither will his advice, however wise in the early stages of a study, ensure successful execution and conclusion. Many a study, launched on the ways of elegant statistical design, later boggled in execution, ends up with results to which the theory of probability can contribute little." (W Edwards Deming, "Principles of Professional Statistical Practice", Annals of Mathematical Statistics, 36(6), 1965)
"The statistician cannot excuse himself from the duty of getting his head clear on the principles of scientific inference, but equally no other thinking man can avoid a like obligation." (Sir Ronald A Fisher, "The Design of Experiments", 1971)
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