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'If data analysis is to be well done, much of it must be a matter of judgment, and <e2><80><98>theory<e2><80><99> whether statistical or non-statistical, will have to guide, not command.' in object 'quotes'
'An inference, if it is to have scientific value, must constitute a prediction concerning future data. If the inference is to be made purely with the help of the distribution theory of statistics, the experiments that constitute evidence for the inference must arise from a state of statistical control; until that state is reached, there is no universe, normal or otherwise, and the statistician<e2><80><99>s calculations by themselves are an illusion if not a delusion.' in object 'quotes'
'If you can<e2><80><99>t have an experiment, do the best you can with whatever data you can gather, but do be very skeptical of historical data and subject them to all the logical tests you can think of.' in object 'quotes'
'Remember that even random coin flips can yield striking, even stunning, patterns that mean nothing at all. When someone shows you a pattern, no matter how impressive the person<e2><80><99>s credentials, consider the possibility that the pattern is just a coincidence. Ask why, not what. No matter what the pattern, the question is: Why should we expect to find this pattern?' in object 'quotes'
'[In statistics] you have the fact that the concepts are not very clean. The idea of probability, of randomness, is not a clean mathematical idea. You cannot produce random numbers mathematically. They can only be produced by things like tossing dice or spinning a roulette wheel. With a formula, any formula, the number you get would be predictable and therefore not random. So as a statistician you have to rely on some conception of a world where things happen in some way at random, a conception which mathematicians don<e2><80><99>t have.' in object 'quotes'
'The statistician<e2><80><99>s job is to draw general conclusions from fragmentary data. Too often the data supplied to him for analysis are not only fragmentary but positively incoherent, so that he can do next to nothing with them. Even the most kindly statistician swears heartily under his breath whenever this happens.' in object 'quotes'
'Just as by <e2><80><98>literacy<e2><80><99>, in this context, we mean much more than its dictionary sense of the ability to read and write, so by <e2><80><98>numeracy<e2><80><99> we mean more than mere ability to manipulate the rule of three. When we say that a scientist is <e2><80><98>illiterate<e2><80><99>, we mean that he is not well enough read to be able to communicate effectively with those who have had a literary education. When we say that a historian or a linguist is <e2><80><98>innumerate<e2><80><99> we mean that he cannot even begin to understand what scientists and mathematicians are talking about.' in object 'quotes'
'To be numerate means to be competent, confident, and comfortable with one<e2><80><99>s judgements on whether to use mathematics in a particular situation and if so, what mathematics to use, how to do it, what degree of accuracy is appropriate, and what the answer means in relation to the context.' in object 'quotes'
'A statistical estimate may be good or bad, accurate or the reverse; but in almost all cases it is likely to be more accurate than a casual observer<e2><80><99>s impression, and the nature of things can only be disproved by statistical methods.' in object 'quotes'
'There is no such thing as randomness. No one who could detect every force operating on a pair of dice would ever play dice games, because there would never be any doubt about the outcome. The randomness, such as it is, applies to our ignorance of the possible outcomes. It doesn<e2><80><99>t apply to the outcomes themselves. They are 100% determined and are not random in the slightest. Scientists have become so confused by this that they now imagine that things really do happen randomly, i.e. for no reason at all.' in object 'quotes'
'The moment you forecast you know you<e2><80><99>re going to be wrong, you just don<e2><80><99>t know when and in which direction.' in object 'quotes'
'If a man stands with his left foot on a hot stove and his right foot in a refrigerator, the statistician would say that, on the average, he<e2><80><99>s comfortable.' in object 'quotes'
'Even properly done statistics can<e2><80><99>t be trusted. The plethora of available statistical techniques and analyses grants researchers an enormous amount of freedom when analyzing their data, and it is trivially easy to <e2><80><98>torture the data until it confesses<e2><80><99>.' in object 'quotes'
'The closer that sample-selection procedures approach the gold standard of random selection - for which the definition is that every individual in the population has an equal chance of appearing in the sample - the more we should trust them. If we don<e2><80><99>t know whether a sample is random, any statistical measure we conduct may be biased in some unknown way.' in object 'quotes'
'The fact must be expressed as data, but there is a problem in that the correct data is difficult to catch. So that I always say 'When you see the data, doubt it!' 'When you see the measurement instrument, doubt it!' [...]For example, if the methods such as sampling, measurement, testing and chemical analysis methods were incorrect, data. [<e2><80><a6>] to measure true characteristics and in an unavoidable case, using statistical sensory test and express them as data.' in object 'quotes'
'We would wish <e2><80><98>numerate<e2><80><99> to imply the possession of two attributes. The first of these is an <e2><80><98>at-homeness<e2><80><99> with numbers and an ability to make use of mathematical skills which enable an individual to cope with the practical mathematical demands of his everyday life. The second is ability to have some appreciation and understanding of information which is presented in mathematical terms, for instance in graphs, charts or tables or by reference to percentage increase or decrease.' in object 'quotes'
'Since all models are wrong the scientist cannot obtain a <e2><80><98>correct<e2><80><99> one by excessive elaboration. On the contrary following William of Occam he should seek an economical description of natural phenomena. Just as the ability to devise simple but evocative models is the signature of the great scientist so overelaboration and overparameterization is often the mark of mediocrity.' in object 'quotes'
'When looking at the end result of any statistical analysis, one must be very cautious not to over interpret the data. Care must be taken to know the size of the sample, and to be certain the method for gathering information is consistent with other samples gathered. [<e2><80><a6>] No one should ever base conclusions without knowing the size of the sample and how random a sample it was. But all too often such data is not mentioned when the statistics are given - perhaps it is overlooked or even intentionally omitted.' in object 'quotes'
'The Drunkard<e2><80><99>s Walk: How Randomness Rules Our Lives, 2008' in object 'quotes'
'Comment on <e2><80><98>Model uncertainty, data mining and statistical inference<e2><80><99>, Journal of the Royal Statistical Society, Series A 158, 1995.' in object 'quotes'