document_title: History of statistics

question_text: why is the word statistics rooted in the latin for state

question_tokens: why is the word statistics rooted in the latin for state

text: History of statistics

text: Introduction[edit]

text: By the 18th century, the term "statistics" designated the systematic collection of demographic and economic data by states. For at least two millennia, these data were mainly tabulations of human and material resources that might be taxed or put to military use. In the early 19th century, collection intensified, and the meaning of "statistics" broadened to include the discipline concerned with the collection, summary, and analysis of data. Today, data is collected and statistics are computed and widely distributed in government, business, most of the sciences and sports, and even for many pastimes. Electronic computers have expedited more elaborate statistical computation even as they have facilitated the collection and aggregation of data. A single data analyst may have available a set of data-files with millions of records, each with dozens or hundreds of separate measurements. These were collected over time from computer activity (for example, a stock exchange) or from computerized sensors, point-of-sale registers, and so on. Computers then produce simple, accurate summaries, and allow more tedious analyses, such as those that require inverting a large matrix or perform hundreds of steps of iteration, that would never be attempted by hand. Faster computing has allowed statisticians to develop "computer-intensive" methods which may look at all permutations, or use randomization to look at 10,000 permutations of a problem, to estimate answers that are not easy to quantify by theory alone..

text: The term "mathematical statistics" designates the mathematical theories of probability and statistical inference, which are used in statistical practice. The relation between statistics and probability theory developed rather late, however. In the 19th century, statistics increasingly used probability theory, whose initial results were found in the 17th and 18th centuries, particularly in the analysis of games of chance (gambling). By 1800, astronomy used probability models and statistical theories, particularly the method of least squares. Early probability theory and statistics was systematized in the 19th century and statistical reasoning and probability models were used by social scientists to advance the new sciences of experimental psychology and sociology, and by physical scientists in thermodynamics and statistical mechanics. The development of statistical reasoning was closely associated with the development of inductive logic and the scientific method, which are concerns that move statisticians away from the narrower area of mathematical statistics. Much of the theoretical work was readily available by the time computers were available to exploit them. By the 1970s, Johnson and Kotz produced a four-volume Compendium on Statistical Distributions (First Edition 1969-1972), which is still an invaluable resource.

text: Applied statistics can be regarded as not a field of mathematics but an autonomous mathematical science, like computer science and operations research. Unlike mathematics, statistics had its origins in public administration. Applications arose early in demography and economics; large areas of micro- and macro-economics today are "statistics" with an emphasis on time-series analyses. With its emphasis on learning from data and making best predictions, statistics also has been shaped by areas of academic research including psychological testing, medicine and epidemiology. The ideas of statistical testing have considerable overlap with decision science. With its concerns with searching and effectively presenting data, statistics has overlap with information science and computer science.

text: Etymology[edit]

text: The term statistics is ultimately derived from the New Latin statisticum collegium ("council of state") and the Italian word statista ("statesman" or "politician"). The German Statistik, first introduced by Gottfried Achenwall (1749), originally designated the analysis of data about the state, signifying the "science of state" (then called political arithmetic in English). It acquired the meaning of the collection and classification of data generally in the early 19th century. It was introduced into English in 1791 by Sir John Sinclair when he published the first of 21 volumes titled Statistical Account of Scotland.[1]

text: Thus, the original principal purpose of Statistik was data to be used by governmental and (often centralized) administrative bodies. The collection of data about states and localities continues, largely through national and international statistical services. In particular, censuses provide frequently updated information about the population.

text: The first book to have 'statistics' in its title was "Contributions to Vital Statistics" (1845) by Francis GP Neison, actuary to the Medical Invalid and General Life Office.[citation needed]

text: Origins in probability theory[edit]

text: This section includes a list of references, related reading or external links, but its sources remain unclear because it lacks inline citations. Please help to improve this section by introducing more precise citations. (July 2012) (Learn how and when to remove this template message)

text: Basic forms of statistics have been used since the beginning of civilization. Early empires often collated censuses of the population or recorded the trade in various commodities. The Roman Empire was one of the first states to extensively gather data on the size of the empire's population, geographical area and wealth.

text: The use of statistical methods dates back to least to the 5th century BCE. The historian Thucydides in his History of the Peloponnesian War [2] describes how the Athenians calculated the height of the wall of Platea by counting the number of bricks in an unplastered section of the wall sufficiently near them to be able to count them. The count was repeated several times by a number of soldiers. The most frequent value (in modern terminology - the mode ) so determined was taken to be the most likely value of the number of bricks. Multiplying this value by the height of the bricks used in the wall allowed the Athenians to determine the height of the ladders necessary to scale the walls.

text: In the Indian epic - the Mahabharata (Book 3: The Story of Nala) - King Rtuparna estimated the number of fruit and leaves (2095 fruit and 50,000,000 - five crores - leaves) on two great branches of a Vibhitaka tree by counting them on a single twig. This number was then multiplied by the number of twigs on the branches. This estimate was later checked and found to be very close to the actual number. With knowledge of this method Nala was subsequently able to regain his kingdom.

text: The earliest writing on statistics was found in a 9th-century book entitled: "Manuscript on Deciphering Cryptographic Messages", written by Al-Kindi (801–873 CE). In his book, Al-Kindi gave a detailed description of how to use statistics and frequency analysis to decipher encrypted messages. This text arguably gave rise to the birth of both statistics and cryptanalysis.[3][4]

text: The Trial of the Pyx is a test of the purity of the coinage of the Royal Mint which has been held on a regular basis since the 12th century. The Trial itself is based on statistical sampling methods. After minting a series of coins - originally from ten pounds of silver - a single coin was placed in the Pyx - a box in Westminster Abbey. After a given period - now once a year - the coins are removed and weighed. A sample of coins removed from the box are then tested for purity.

text: The Nuova Cronica, a 14th-century history of Florence by the Florentine banker and official Giovanni Villani, includes much statistical information on population, ordinances, commerce and trade, education, and religious facilities and has been described as the first introduction of statistics as a positive element in history,[5] though neither the term nor the concept of statistics as a specific field yet existed. But this was proven to be incorrect after the rediscovery of Al-Kindi's book on frequency analysis.[3][4]

text: The arithmetic mean, although a concept known to the Greeks, was not generalised to more than two values until the 16th century. The invention of the decimal system by Simon Stevin in 1585 seems likely to have facilitated these calculations. This method was first adopted in astronomy by Tycho Brahe who was attempting to reduce the errors in his estimates of the locations of various celestial bodies.

text: The idea of the median originated in Edward Wright's book on navigation (Certaine Errors in Navigation) in 1599 in a section concerning the determination of location with a compass. Wright felt that this value was the most likely to be the correct value in a series of observations.

text: The birth of statistics is often dated to 1662, when John Graunt, along with William Petty, developed early human statistical and census methods that provided a framework for modern demography. He produced the first life table, giving probabilities of survival to each age. His book Natural and Political Observations Made upon the Bills of Mortality used analysis of the mortality rolls to make the first statistically based estimation of the population of London. He knew that there were around 13,000 funerals per year in London and that three people died per eleven families per year. He estimated from the parish records that the average family size was 8 and calculated that the population of London was about 384,000. Laplace in 1802 estimated the population of France with a similar method.

text: Although the original scope of statistics was limited to data useful for governance, the approach was extended to many fields of a scientific or commercial nature during the 19th century. The mathematical foundations for the subject heavily drew on the new probability theory, pioneered in the 16th century by Gerolamo Cardano, Pierre de Fermat and Blaise Pascal. Christiaan Huygens (1657) gave the earliest known scientific treatment of the subject. Jakob Bernoulli's Ars Conjectandi (posthumous, 1713) and Abraham de Moivre's The Doctrine of Chances (1718) treated the subject as a branch of mathematics. In his book Bernoulli introduced the idea of representing complete certainty as one and probability as a number between zero and one.

text: The formal study of theory of errors may be traced back to Roger Cotes' Opera Miscellanea (posthumous, 1722), but a memoir prepared by Thomas Simpson in 1755 (printed 1756) first applied the theory to the discussion of errors of observation. The reprint (1757) of this memoir lays down the axioms that positive and negative errors are equally probable, and that there are certain assignable limits within which all errors may be supposed to fall; continuous errors are discussed and a probability curve is given. Simpson discussed several possible distributions of error. He first considered the uniform distribution and then the discrete symmetric triangular distribution followed by the continuous symmetric triangle distribution. Tobias Mayer, in his study of the libration of the moon (Kosmographische Nachrichten, Nuremberg, 1750), invented the first formal method for estimating the unknown quantities by generalized the averaging of observations under identical circumstances to the averaging of groups of similar equations.

text: Ruder Boškovic in 1755 based in his work on the shape of the earth proposed in his book De Litteraria expeditione per pontificiam ditionem ad dimetiendos duos meridiani gradus a PP. Maire et Boscovicli that the true value of a series of observations would be that which minimises the sum of absolute errors. In modern terminology this value is the median. The first example of what later became known as the normal curve was studied by Abraham de Moivre who plotted this curve on November 12, 1733.[6] de Moivre was studying the number of heads that occurred when a 'fair' coin was tossed.

text: In 1761 Thomas Bayes proved Bayes' theorem and in 1765 Joseph Priestley invented the first timeline charts.

text: Johann Heinrich Lambert in his 1765 book Anlage zur Architectonic proposed the semicircle as a distribution of errors:

text: with -1 < x < 1.

text: Pierre-Simon Laplace (1774) made the first attempt to deduce a rule for the combination of observations from the principles of the theory of probabilities. He represented the law of probability of errors by a curve and deduced a formula for the mean of three observations.

text: Laplace in 1774 noted that the frequency of an error could be expressed as an exponential function of its magnitude once its sign was disregarded.[7][8] This distribution is now known as the Laplace distribution. Lagrange proposed a parabolic distribution of errors in 1776.

text: Laplace in 1778 published his second law of errors wherein he noted that the frequency of an error was proportional to the exponential of the square of its magnitude. This was subsequently rediscovered by Gauss (possibly in 1795) and is now best known as the normal distribution which is of central importance in statistics.[9] This distribution was first referred to as the normal distribution by Pierce in 1873 who was studying measurement errors when an object was dropped onto a wooden base.[10] He chose the term normal because of its frequent occurrence in naturally occurring variables.

text: Lagrange also suggested in 1781 two other distributions for errors - a Raised cosine distribution and a logarithmic distribution.

text: Laplace gave (1781) a formula for the law of facility of error (a term due to Joseph Louis Lagrange, 1774), but one which led to unmanageable equations. Daniel Bernoulli (1778) introduced the principle of the maximum product of the probabilities of a system of concurrent errors.

text: In 1786 William Playfair (1759-1823) introduced the idea of graphical representation into statistics. He invented the line chart, bar chart and histogram and incorporated them into his works on economics, the Commercial and Political Atlas. This was followed in 1795 by his invention of the pie chart and circle chart which he used to display the evolution of England's imports and exports. These latter charts came to general attention when he published examples in his Statistical Breviary in 1801.

text: Laplace, in an investigation of the motions of Saturn and Jupiter in 1787, generalized Mayer's method by using different linear combinations of a single group of equations.

text: In 1802 Laplace estimated the population of France to be 28,328,612.[11] He calculated this figure using the number of births in the previous year and census data for three communities. The census data of these communities showed that they had 2,037,615 persons and that the number of births were 71,866. Assuming that these samples were representative of France, Laplace produced his estimate for the entire population.

text: The method of least squares, which was used to minimize errors in data measurement, was published independently by Adrien-Marie Legendre (1805), Robert Adrain (1808), and Carl Friedrich Gauss (1809). Gauss had used the method in his famous 1801 prediction of the location of the dwarf planet Ceres. The observations that Gauss based his calculations on were made by the Italian monk Piazzi.

text: The term probable error (der wahrscheinliche Fehler) - the median deviation from the mean - was introduced in 1815 by the German astronomer Frederik Wilhelm Bessel. Antoine Augustin Cournot in 1843 was the first to use the term median (valeur médiane) for the value that divides a probability distribution into two equal halves.

text:
Other contributors to the theory of errors were Ellis (1844), De Morgan (1864), Glaisher (1872), and Giovanni Schiaparelli (1875).[citation needed] Peters's (1856) formula for

r

{\displaystyle r}

, the "probable error" of a single observation was widely used and inspired early robust statistics (resistant to outliers: see Peirce's criterion).

text: In the 19th century authors on statistical theory included Laplace, S. Lacroix (1816), Littrow (1833), Dedekind (1860), Helmert (1872), Laurent (1873), Liagre, Didion, De Morgan and Boole.

text: Gustav Theodor Fechner used the median (Centralwerth) in sociological and psychological phenomena.[12] It had earlier been used only in astronomy and related fields. Francis Galton used the English term median for the first time in 1881 having earlier used the terms middle-most value in 1869 and the medium in 1880.[13]

text: Adolphe Quetelet (1796–1874), another important founder of statistics, introduced the notion of the "average man" (l'homme moyen) as a means of understanding complex social phenomena such as crime rates, marriage rates, and suicide rates.[14]

text: The first tests of the normal distribution were invented by the German statistician Wilhelm Lexis in the 1870s. The only data sets available to him that he was able to show were normally distributed were birth rates.

text: Development of modern statistics[edit]

text: Although the origins of statistical theory lie in the 18th century advances in probability, the modern field of statistics only emerged in the late 19th and early 20th century in three stages. The first wave, at the turn of the century, was led by the work of Francis Galton and Karl Pearson, who transformed statistics into a rigorous mathematical discipline used for analysis, not just in science, but in industry and politics as well. The second wave of the 1910s and 20s was initiated by William Gosset, and reached its culmination in the insights of Ronald Fisher. This involved the development of better design of experiments models, hypothesis testing and techniques for use with small data samples. The final wave, which mainly saw the refinement and expansion of earlier developments, emerged from the collaborative work between Egon Pearson and Jerzy Neyman in the 1930s.[15] Today, statistical methods are applied in all fields that involve decision making, for making accurate inferences from a collated body of data and for making decisions in the face of uncertainty based on statistical methodology.

text: The first statistical bodies were established in the early 19th century. The Royal Statistical Society was founded in 1834 and Florence Nightingale, its first female member, pioneered the application of statistical analysis to health problems for the furtherance of epidemiological understanding and public health practice. However, the methods then used would not be considered as modern statistics today.

text: The Oxford scholar Francis Ysidro Edgeworth's book, Metretike: or The Method of Measuring Probability and Utility (1887) dealt with probability as the basis of inductive reasoning, and his later works focused on the 'philosophy of chance'.[16] His first paper on statistics (1883) explored the law of error (normal distribution), and his Methods of Statistics (1885) introduced an early version of the t distribution, the Edgeworth expansion, the Edgeworth series, the method of variate transformation and the asymptotic theory of maximum likelihood estimates.

text: The Norwegian Anders Nicolai Kiær introduced the concept of stratified sampling in 1895.[17] Arthur Lyon Bowley introduced new methods of data sampling in 1906 when working on social statistics. Although statistical surveys of social conditions had started with Charles Booth's "Life and Labour of the People in London" (1889-1903) and Seebohm Rowntree's "Poverty, A Study of Town Life" (1901), Bowley's, key innovation consisted of the use of random sampling techniques. His efforts culminated in his New Survey of London Life and Labour.[18]

text: Francis Galton is credited as one of the principal founders of statistical theory. His contributions to the field included introducing the concepts of standard deviation, correlation, regression and the application of these methods to the study of the variety of human characteristics - height, weight, eyelash length among others. He found that many of these could be fitted to a normal curve distribution.[19]

text: Galton submitted a paper to Nature in 1907 on the usefulness of the median.[20] He examined the accuracy of 787 guesses of the weight of an ox at a country fair. The actual weight was 1208 pounds: the median guess was 1198. The guesses were markedly non-normally distributed.

text: Galton's publication of Natural Inheritance in 1889 sparked the interest of a brilliant mathematician, Karl Pearson,[21] then working at University College London, and he went on to found the discipline of mathematical statistics.[22] He emphasised the statistical foundation of scientific laws and promoted its study and his laboratory attracted students from around the world attracted by his new methods of analysis, including Udny Yule. His work grew to encompass the fields of biology, epidemiology, anthropometry, medicine and social history. In 1901, with Walter Weldon, founder of biometry, and Galton, he founded the journal Biometrika as the first journal of mathematical statistics and biometry.

text: His work, and that of Galton's, underpins many of the 'classical' statistical methods which are in common use today, including the Correlation coefficient, defined as a product-moment;[23] the method of moments for the fitting of distributions to samples; Pearson's system of continuous curves that forms the basis of the now conventional continuous probability distributions; Chi distance a precursor and special case of the Mahalanobis distance[24] and P-value, defined as the probability measure of the complement of the ball with the hypothesized value as center point and chi distance as radius.[24] He also introduced the term 'standard deviation'.

text: He also founded the statistical hypothesis testing theory,[24] Pearson's chi-squared test and principal component analysis.[25][26] In 1911 he founded the world's first university statistics department at University College London.

text: The second wave of mathematical statistics was pioneered by Ronald Fisher who wrote two textbooks, Statistical Methods for Research Workers, published in 1925 and The Design of Experiments in 1935, that were to define the academic discipline in universities around the world. He also systematized previous results, putting them on a firm mathematical footing. In his 1918 seminal paper The Correlation between Relatives on the Supposition of Mendelian Inheritance, the first use to use the statistical term, variance. In 1919, at Rothamsted Experimental Station he started a major study of the extensive collections of data recorded over many years. This resulted in a series of reports under the general title Studies in Crop Variation. In 1930 he published The Genetical Theory of Natural Selection where he applied statistics to evolution.

text: Over the next seven years, he pioneered the principles of the design of experiments (see below) and elaborated his studies of analysis of variance. He furthered his studies of the statistics of small samples. Perhaps even more important, he began his systematic approach of the analysis of real data as the springboard for the development of new statistical methods. He developed computational algorithms for analyzing data from his balanced experimental designs. In 1925, this work resulted in the publication of his first book, Statistical Methods for Research Workers.[28] This book went through many editions and translations in later years, and it became the standard reference work for scientists in many disciplines. In 1935, this book was followed by The Design of Experiments, which was also widely used.

text: In addition to analysis of variance, Fisher named and promoted the method of maximum likelihood estimation. Fisher also originated the concepts of sufficiency, ancillary statistics, Fisher's linear discriminator and Fisher information. His article On a distribution yielding the error functions of several well known statistics (1924) presented Pearson's chi-squared test and William Gosset's t in the same framework as the Gaussian distribution, and his own parameter in the analysis of variance Fisher's z-distribution (more commonly used decades later in the form of the F distribution).[29] The 5% level of significance appears to have been introduced by Fisher in 1925.[30] Fisher stated that deviations exceeding twice the standard deviation are regarded as significant. Before this deviations exceeding three times the probable error were considered significant. For a symmetrical distribution the probable error is half the interquartile range. For a normal distribution the probable error is approximately 2/3 the standard deviation. It appears that Fisher's 5% criterion was rooted in previous practice.

text: Other important contributions at this time included Charles Spearman's rank correlation coefficient that was a useful extension of the Pearson correlation coefficient. William Sealy Gosset, the English statistician better known under his pseudonym of Student, introduced Student's t-distribution, a continuous probability distribution useful in situations where the sample size is small and population standard deviation is unknown.

text: Egon Pearson (Karl's son) and Jerzy Neyman introduced the concepts of "Type II" error, power of a test and confidence intervals. Jerzy Neyman in 1934 showed that stratified random sampling was in general a better method of estimation than purposive (quota) sampling.[31]

text: Design of experiments[edit]

text: This section relies too much on references to primary sources. Please improve this section by adding secondary or tertiary sources. (February 2012) (Learn how and when to remove this template message)

text: In 1747, while serving as surgeon on HM Bark Salisbury, James Lind carried out a controlled experiment to develop a cure for scurvy.[32] In this study his subjects' cases "were as similar as I could have them", that is he provided strict entry requirements to reduce extraneous variation. The men were paired, which provided blocking. From a modern perspective, the main thing that is missing is randomized allocation of subjects to treatments.

text: Lind is today often described as a one-factor-at-a-time experimenter.[33] Similar one-factor-at-a-time (OFAT) experimentation was performed at the Rothamsted Research Station in the 1840s by Sir John Lawes to determine the optimal inorganic fertilizer for use on wheat.[33]

text: A theory of statistical inference was developed by Charles S. Peirce in "Illustrations of the Logic of Science" (1877–1878) and "A Theory of Probable Inference" (1883), two publications that emphasized the importance of randomization-based inference in statistics. In another study, Peirce randomly assigned volunteers to a blinded, repeated-measures design to evaluate their ability to discriminate weights.[34][35][36][37]

text: Peirce's experiment inspired other researchers in psychology and education, which developed a research tradition of randomized experiments in laboratories and specialized textbooks in the 1800s.[34][35][36][37] Peirce also contributed the first English-language publication on an optimal design for regression-models in 1876.[38] A pioneering optimal design for polynomial regression was suggested by Gergonne in 1815.[citation needed] In 1918 Kirstine Smith published optimal designs for polynomials of degree six (and less).[39]

text: The use of a sequence of experiments, where the design of each may depend on the results of previous experiments, including the possible decision to stop experimenting, was pioneered[40] by Abraham Wald in the context of sequential tests of statistical hypotheses.[41] Surveys are available of optimal sequential designs,[42] and of adaptive designs.[43] One specific type of sequential design is the "two-armed bandit", generalized to the multi-armed bandit, on which early work was done by Herbert Robbins in 1952.[44]

text: The term "design of experiments" (DOE) derives from early statistical work performed by Sir Ronald Fisher. He was described by Anders Hald as "a genius who almost single-handedly created the foundations for modern statistical science."[45] Fisher initiated the principles of design of experiments and elaborated on his studies of "analysis of variance". Perhaps even more important, Fisher began his systematic approach to the analysis of real data as the springboard for the development of new statistical methods. He began to pay particular attention to the labour involved in the necessary computations performed by hand, and developed methods that were as practical as they were founded in rigour. In 1925, this work culminated in the publication of his first book, Statistical Methods for Research Workers.[46] This went into many editions and translations in later years, and became a standard reference work for scientists in many disciplines.[47]

text: A methodology for designing experiments was proposed by Ronald A. Fisher, in his innovative book The Design of Experiments (1935) which also became a standard.[48][49][50][51] As an example, he described how to test the hypothesis that a certain lady could distinguish by flavour alone whether the milk or the tea was first placed in the cup. While this sounds like a frivolous application, it allowed him to illustrate the most important ideas of experimental design: see Lady tasting tea.

text: Agricultural science advances served to meet the combination of larger city populations and fewer farms. But for crop scientists to take due account of widely differing geographical growing climates and needs, it was important to differentiate local growing conditions. To extrapolate experiments on local crops to a national scale, they had to extend crop sample testing economically to overall populations. As statistical methods advanced (primarily the efficacy of designed experiments instead of one-factor-at-a-time experimentation), representative factorial design of experiments began to enable the meaningful extension, by inference, of experimental sampling results to the population as a whole.[citation needed] But it was hard to decide how representative was the crop sample chosen.[citation needed] Factorial design methodology showed how to estimate and correct for any random variation within the sample and also in the data collection procedures.

text: Bayesian statistics[edit]

text: The term Bayesian refers to Thomas Bayes (1702–1761), who proved a special case of what is now called Bayes' theorem. However it was Pierre-Simon Laplace (1749–1827) who introduced a general version of the theorem and applied it to celestial mechanics, medical statistics, reliability, and jurisprudence.[52] When insufficient knowledge was available to specify an informed prior, Laplace used uniform priors, according to his "principle of insufficient reason".[52][53] Laplace assumed uniform priors for mathematical simplicity rather than for philosophical reasons.[52] Laplace also introduced[citation needed] primitive versions of conjugate priors and the theorem of von Mises and Bernstein, according to which the posteriors corresponding to initially differing priors ultimately agree, as the number of observations increases.[54] This early Bayesian inference, which used uniform priors following Laplace's principle of insufficient reason, was called "inverse probability" (because it infers backwards from observations to parameters, or from effects to causes[55]).

text: After the 1920s, inverse probability was largely supplanted[citation needed] by a collection of methods that were developed by Ronald A. Fisher, Jerzy Neyman and Egon Pearson. Their methods came to be called frequentist statistics.[55] Fisher rejected the Bayesian view, writing that "the theory of inverse probability is founded upon an error, and must be wholly rejected".[56] At the end of his life, however, Fisher expressed greater respect for the essay of Bayes, which Fisher believed to have anticipated his own, fiducial approach to probability; Fisher still maintained that Laplace's views on probability were "fallacious rubbish".[56] Neyman started out as a "quasi-Bayesian", but subsequently developed confidence intervals (a key method in frequentist statistics) because "the whole theory would look nicer if it were built from the start without reference to Bayesianism and priors".[57] The word Bayesian appeared around 1950, and by the 1960s it became the term preferred by those dissatisfied with the limitations of frequentist statistics.[55][58]

text: In the 20th century, the ideas of Laplace were further developed in two different directions, giving rise to objective and subjective currents in Bayesian practice. In the objectivist stream, the statistical analysis depends on only the model assumed and the data analysed.[59] No subjective decisions need to be involved. In contrast, "subjectivist" statisticians deny the possibility of fully objective analysis for the general case.

text: In the further development of Laplace's ideas, subjective ideas predate objectivist positions. The idea that 'probability' should be interpreted as 'subjective degree of belief in a proposition' was proposed, for example, by John Maynard Keynes in the early 1920s.[citation needed] This idea was taken further by Bruno de Finetti in Italy (Fondamenti Logici del Ragionamento Probabilistico, 1930) and Frank Ramsey in Cambridge (The Foundations of Mathematics, 1931).[60] The approach was devised to solve problems with the frequentist definition of probability but also with the earlier, objectivist approach of Laplace.[59] The subjective Bayesian methods were further developed and popularized in the 1950s by L.J. Savage.[citation needed]

text: Objective Bayesian inference was further developed by Harold Jeffreys at the University of Cambridge. His seminal book "Theory of probability" first appeared in 1939 and played an important role in the revival of the Bayesian view of probability.[61][62] In 1957, Edwin Jaynes promoted the concept of maximum entropy for constructing priors, which is an important principle in the formulation of objective methods, mainly for discrete problems. In 1965, Dennis Lindley's 2-volume work "Introduction to Probability and Statistics from a Bayesian Viewpoint" brought Bayesian methods to a wide audience. In 1979, José-Miguel Bernardo introduced reference analysis,[59] which offers a general applicable framework for objective analysis.[63] Other well-known proponents of Bayesian probability theory include I.J. Good, B.O. Koopman, Howard Raiffa, Robert Schlaifer and Alan Turing.

text: In the 1980s, there was a dramatic growth in research and applications of Bayesian methods, mostly attributed to the discovery of Markov chain Monte Carlo methods, which removed many of the computational problems, and an increasing interest in nonstandard, complex applications.[64] Despite growth of Bayesian research, most undergraduate teaching is still based on frequentist statistics.[65] Nonetheless, Bayesian methods are widely accepted and used, such as for example in the field of machine learning.[66]

text: Important contributors to statistics[edit]

text:
Thomas Bayes
George E. P. Box
Pafnuty Chebyshev
David R. Cox
Gertrude Cox
Harald Cramér
Francis Ysidro Edgeworth
Bradley Efron
Bruno de Finetti
Ronald A. Fisher
Francis Galton

Carl Friedrich Gauss
William Sealey Gosset ("Student")
Andrey Kolmogorov
Pierre-Simon Laplace
Erich L. Lehmann
Aleksandr Lyapunov
Anil Kumar Gain
Prasanta Chandra Mahalanobis
Abraham De Moivre
Jerzy Neyman
Florence Nightingale

Blaise Pascal
Karl Pearson
Charles S. Peirce
Adolphe Quetelet
C. R. Rao
Walter A. Shewhart
Charles Spearman
Charles Stein
Thorvald N. Thiele
John Tukey
Abraham Wald


document_title: Home key

question_text: what is the function of home key in computer

root

text: Home key

text: Microsoft Windows[edit]

text: In modern Microsoft Windows text editing applications, it is primarily used to return the cursor to the beginning of the line where the cursor is located. When the text is not editable, the Home key is used to return to the beginning of the document; this can also be done in editable text if the key is pressed along with Control.

tag: p

text: The Home key can also be used to select all the characters before the cursor in a certain line if pressed along with ⇧ Shift in selectable text.

text: macOS[edit]

text: Only full-sized Apple keyboards have a Home key. On most macOS applications, the key works like the original on UNIX in the days of dumb-terminals, where Home moves to the start of a document. When the key is pressed, the window scrolls to the top, while the caret position does not change at all; that is, the Home key is tied to the current window, not the text box being edited.[1][2] On Apple keyboards that do not have a Home key, one can press Fn+← for the Home key functionality described above.  To get the same result as the Windows platform (that is, moving the insertion point to the beginning of the current line of text), one can press  ⌘ Command+←. An application can also be used to change this behaviour.[3]

text: Linux[edit]

text: In Linux, the Home key has basically the same functionality as it does on Windows. It returns the cursor to the beginning of the line in editable text, and otherwise scrolls a scrollable document to the beginning. Also, like Windows, the Home key can be used to select all the characters before the cursor in a certain line if pressed along with ⇧ Shift in editable text.

text: Non-GUI applications[edit]

text: In older screen-oriented, text-based (non-GUI) applications, the user often accessed the "screen" they wanted through a series of menu screens with numbered options. The Home key took the user to the "top" menu screen.


document_title: X-ray tube

question_text: where is radiation produced in the xray tube

text: X-ray tube

text: Types[edit]

text: Rotating anode tube[edit]

text:
A: Anode
C: cathode
T: Anode target
W: X-ray window

tag: ul

text: The anode is supported on vacuum bearings and can be rotated by electromagnetic induction from a series of stator windings outside the evacuated tube. Typically, eddy currents are induced in a rotatable metal cylinder, the rotor. The superimposition of external magnetic induction and induction from the eddy currents, which changes direction with time, creates a driving mechanical momentum in the rotor.[clarification needed]

text: Because the entire anode assembly has to be contained within the evacuated tube, heat removal is a serious problem, further exacerbated by the higher power rating available. Due to the high heat generation, a matched thermal expansion of glass and the anode material is necessary. For this, high-borate borosilicate glass pioneered by Otto Schott is often used. Direct cooling by conduction or convection, as in the Coolidge tube, is difficult. In most tubes, the anode is suspended on ball bearings with silver powder lubrication which provides almost negligible cooling by conduction.

text: A recent development has been liquid gallium lubricated fluid dynamic bearings which can withstand very high temperatures without contaminating the tube vacuum. The large bearing contact surface and metal lubricant provide an effective method for conduction of heat from the anode.

text: The anode must be constructed of high temperature materials. The focal spot temperature can reach 2,500 °C (4,530 °F) during an exposure, and the anode assembly can reach 1,000 °C (1,830 °F) following a series of large exposures. Typical materials are a tungsten-rhenium target on a molybdenum core, backed with graphite. The rhenium makes the tungsten more ductile and resistant to wear from the impact of the electron beams. The molybdenum conducts heat from the target. The graphite provides thermal storage for the anode, and minimizes the rotating mass of the anode.

text: Increasing demand for high-performance Computed tomography (CT) scanning and angiography systems has driven development of very high performance medical X-ray tubes. Contemporary CT tubes have power ratings of up to 100 kW and anode heat capacity of 6 MJ, yet retain an effective focal spot area of less than 1 mm2.

text: Microfocus X-ray tube[edit]

text: Some X-ray examinations (such as, e.g., non-destructive testing and 3-D microtomography) need very high-resolution images and therefore require X-ray tubes that can generate very small focal spot sizes, typically below 50 µm in diameter. These tubes are called microfocus X-ray tubes.

text: There are two basic types of microfocus X-ray tubes: solid-anode tubes and metal-jet-anode tubes.

text: Solid-anode microfocus X-ray tubes are in principle very similar to the Coolidge tube, but with the important distinction that care has been taken to be able to focus the electron beam into a very small spot on the anode. Many microfocus X-ray sources operate with focus spots in the range 5-20 µm, but in the extreme cases spots smaller than 1 µm may be produced.

text: The major drawback of solid-anode microfocus X-ray tubes is the very low power they operate at. In order to avoid melting of the anode the electron-beam power density must be below a maximum value. This value is somewhere in the range 0.4-0.8 W/µm depending on the anode material.[2] This means that a solid-anode microfocus source with a 10 µm electron-beam focus can operate at a power in the range 4-8 W.

text: In metal-jet-anode microfocus X-ray tubes the solid metal anode is replaced with a jet of liquid metal, which acts as the electron-beam target. The advantage of the metal-jet anode is that the maximum electron-beam power density is significantly increased. Values in the range 3-6 W/µm have been reported for different anode materials (gallium and tin).[3][4] In the case with a 10 µm electron-beam focus a metal-jet-anode microfocus X-ray source may operate at 30-60 W.

text: The major benefit of the increased power density level for the metal-jet X-ray tube is the possibility to operate with a smaller focal spot, say 5 µm, to increase image resolution and at the same time acquire the image faster, since the power is higher (15-30 W) than for solid-anode tubes with 10 µm focal spots.

text: Physics[edit]

text: As with any vacuum tube, there is a cathode, which emits electrons into the vacuum and an anode to collect the electrons, thus establishing a flow of electrical current, known as the beam, through the tube. A high voltage power source, for example 30 to 150 kilovolts (kV), is connected across cathode and anode to accelerate the electrons. The X-ray spectrum depends on the anode material and the accelerating voltage.[5]

text: In many applications, the current flow (typically in the range 1 mA to 1 A) is able to be pulsed on for between about 1 ms to 1 s. This enables consistent doses of X-rays, and taking snapshots of motion. Until the late 1980s, X-ray generators were merely high-voltage, AC to DC variable power supplies. In the late 1980s a different method of control was emerging, called high speed switching. This followed the electronics technology of switching power supplies (aka switch mode power supply), and allowed for more accurate control of the X-ray unit, higher quality results, and reduced X-ray exposures.

text: Electrons from the cathode collide with the anode material, usually tungsten, molybdenum or copper, and accelerate other electrons, ions and nuclei within the anode material. About 1% of the energy generated is emitted/radiated, usually perpendicular to the path of the electron beam, as X-rays. The rest of the energy is released as heat. Over time, tungsten will be deposited from the target onto the interior surface of the tube, including the glass surface. This will slowly darken the tube and was thought to degrade the quality of the X-ray beam. Vaporized tungsten condenses on the inside of the envelope over the "window" and thus acts as an additional filter and decreases the tubes ability to radiate heat.[6] Eventually, the tungsten deposit may become sufficiently conductive that at high enough voltages, arcing occurs. The arc will jump from the cathode to the tungsten deposit, and then to the anode. This arcing causes an effect called "crazing" on the interior glass of the X-ray window. As time goes on, the tube becomes unstable even at lower voltages, and must be replaced. At this point, the tube assembly (also called the "tube head") is removed from the X-ray system, and replaced with a new tube assembly. The old tube assembly is shipped to a company that reloads it with a new X-ray tube.

text: The X-ray photon-generating effect is generally called the bremsstrahlung effect, a contraction of the German bremsen for braking, and strahlung for radiation.

text: The range of photonic energies emitted by the system can be adjusted by changing the applied voltage, and installing aluminum filters of varying thicknesses. Aluminum filters are installed in the path of the X-ray beam to remove "soft" (non-penetrating) radiation. The number of emitted X-ray photons, or dose, are adjusted by controlling the current flow and exposure time.

text: The tube current and exposure time affect the dose and therefore the contrast of the image.

text: Heat unit[edit]

text: Since the introduction of scattered electron traps, directly cooled liquid metal anode bearings, rotating frame tubes and other modern technology the term has become misleading when used for the objective comparison of the performance of medical rotating anode X-ray tubes. Accordingly, the IEC 60613 standard has been revised in 2010. Anode heat storage capacity and implicitly "Heat Units" were abandoned and replaced by terms of practical relevance, e.g. NOMINAL CT ANODE INPUT POWER. Historically, heat units were referring to the amount of heat stored in a solely radiation cooled anode inside an electron reflecting glass envelope. In radiography, in particular in radiology, a heat unit was a usual unit derived from the Joule and measuring the quantity of heat in a device, in particular the thermal energy that an X-ray tube must be able to support and dissipate during and after an exam.

text: Historically, this unit comes from the need to express a quantity of energy whatever the waveform of the electrical source power (direct or pulsating). The heat produced in these devices is (in Joule) :

text:
In radiography voltage is usually expressed in

k

V

p

{\displaystyle \mathrm {kV_{p}} }

 (thousands of volts peak), the effective current in mA and the time in seconds:

text:
w being the waveform ratio. With a full-wave rectification of a sine wave it equals

1

2

≈
0.707

{\displaystyle {\frac {1}{\sqrt {2}}}\approx 0.707}

, thus the practical unit:

text: History[edit]

text: Crookes tube[edit]

text: Historically, X-rays were discovered radiating from experimental discharge tubes called Crookes tubes invented by British physicist William Crookes and others. As the medical and other uses of X-rays became apparent, workshops began to manufacture specialized Crookes tubes to produce X-rays. These were the first X-ray tubes. These first generation cold cathode or Crookes X-ray tubes were used until the 1920s.

text: Crookes tubes generated the electrons needed to create X-rays by ionization of the residual air in the tube, instead of a heated filament, so they were partially but not completely evacuated. They consisted of a glass bulb with around 10−6 to 5×10−8 atmospheric pressure of air (0.1 to 0.005 Pa). An aluminum cathode plate at one end of the tube created a beam of electrons, which struck a platinum anode (for economy, made from nickel or copper with a thin platinum face)[8] target at the center generating X-rays. The anode surface was angled so that the X-rays would radiate through the side of the tube. The cathode was concave so that the electrons were focused on a small (~1 mm) spot on the anode, approximating a point source of X-rays, which resulted in sharper images. The tube had a third electrode, an anticathode connected to the anode. It improved the X-ray output, but the method by which it achieved this is not understood. A more common arrangement used a copper plate anticathode (similar in construction to the cathode) in line with the anode such that the anode was between the cathode and the anticathode.

text: To operate, a DC voltage of a few kilovolts to as much as 100 kV was applied between the anodes and the cathode, usually generated by an induction coil, or for larger tubes, an electrostatic machine. This created and then accelerated a small number of ions from the low pressure gas in the tube. These struck further gas atoms, knocking electrons off them, creating more positive ions in a chain reaction. All the positive ions were attracted to the cathode. When they struck it, they knocked electrons out of the metal, which were accelerated along with the electrons knocked from the gas atoms toward the anode target. When these high speed electrons struck the atoms of the anode, they created X-rays by one of two processes, either Bremsstrahlung or X-ray fluorescence.

text: Crookes tubes were unreliable. As time passed, the residual air would be absorbed by the walls of the tube, reducing the pressure. This increased the voltage across the tube, generating 'harder' X-rays, until eventually the tube stopped working. To prevent this, 'softener' devices were used (see picture). A small tube attached to the side of the main tube contained a mica sleeve or chemical that released a small amount of gas when heated, restoring the correct pressure.

text: The glass envelope of the tube would blacken in use due to the X-rays affecting its structure.

text: Coolidge tube[edit]

text:
C: filament/cathode (-)
A: anode (+)
Win and Wout: water inlet and outlet of the cooling device

text: The Crookes tube was improved by William Coolidge in 1913.[9] The Coolidge tube, also called hot cathode tube, is the most widely used. It works with a very good quality vacuum (about 10−4 Pa, or 10−6 Torr).

text: In the Coolidge tube, the electrons are produced by thermionic effect from a tungsten filament heated by an electric current. The filament is the cathode of the tube. The high voltage potential is between the cathode and the anode, the electrons are thus accelerated, and then hit the anode.

text: There are two designs: end-window tubes and side-window tubes. End window tubes usually have "transmission target" which is thin enough to allow X-rays to pass through the target (X-rays are emitted in the same direction as the electrons are moving.) In one common type of end-window tube, the filament is around the anode ("annular" or ring-shaped), the electrons have a curved path (half of a toroid).

text: What is special about side-window tubes is an electrostatic lens is used to focus the beam onto a very small spot on the anode. The anode is specially designed to dissipate the heat and wear resulting from this intense focused barrage of electrons. Some anodes are mechanically spun to increase the area heated by the beam (e.g. edical "rotating anode") or cooled by circulating coolant (indirectly on most rotating anodes). The anode is precisely angled at 1-20 degrees off perpendicular to the electron current so as to allow the escape of some of the X-ray photons which are emitted perpendicular to the direction of the electron current. The anode is usually made out of tungsten or molybdenum. The tube has a window designed for escape of the generated X-ray photons.

text: The power of a Coolidge tube usually ranges from 0.1 to 18 kW.

text: Hazards of X-ray production from vacuum tubes[edit]

text: Any vacuum tube operating at several thousand volts or more can produce X-rays as an unwanted byproduct, raising safety issues.[10][11] The higher the voltage, the more penetrating the resulting radiation and the more the hazard. CRT displays, once common in color televisions and computer displays, operate at 3-40 kilovolts,[12] making them the main concern among household appliances. Historically, concern has focused less on the cathode ray tube, since its thick glass envelope is impregnated with several pounds of lead for shielding, than on high voltage (HV) rectifier and voltage regulator tubes inside. In the late 1960s it was found that a failure in the HV supply circuit of some General Electric TVs could leave excessive voltages on the regulator tube, causing it to emit X-rays.[citation needed] The models were recalled and the ensuing scandal caused the US agency responsible for regulating this hazard, the Center for Devices and Radiological Health of the Food and Drug Administration (FDA), to require that all TVs include circuits to prevent excessive voltages in the event of failure.[citation needed] The hazard associated with excessive voltages was eliminated with the advent of all solid state TVs, which have no tubes beside the CRT. Since 1969 the FDA has limited TV X-ray emission to 0.5 mR (milliroentgen) per hour. The flat screens used today do not have any vacuum tubes capable of emitting X-rays.


document_title: Eddie the Eagle (film)

question_text: who plays eddie the eagle in the movie

question_tokens: who plays eddie the eagle in the movie

text: Eddie the Eagle (film)

text: Plot[edit]

text: In 1973, ten-year-old Eddie Edwards dreams of Olympic glory, practicing in various Olympic events and failing miserably. His mother unconditionally supports him, while his father constantly discourages him. As a young teen, he gives up his dream of participating in the Summer Games in favour of skiing in the Winter Games. Although successful at the sport, he is rejected by British Olympic officials for being uncouth. Realizing he could make the team as a ski jumper (a sport in which the United Kingdom had not participated in six decades), he decamps to a training facility in Garmisch-Partenkirchen, Germany. The more seasoned jumpers, specifically those on the Norwegian team, belittle him.

text: He self-trains, and after successfully completing the 15-metre (49 ft) hill on his first try, he injures himself on his first try from a 40-metre (130 ft) hill. Alcoholic snow groomer Bronson Peary encourages Eddie to give up, but Eddie's tenacious spirit and shared feelings of ostracism by the other jumpers there convince him to train Eddie. Peary is a former champion American ski jumper who left the sport in his 20s after a conflict with his mentor, famous ski jumper Warren Sharp, which Eddie learns from Petra, the kindly owner of a nearby tavern. With very little time to qualify for the 1988 Winter Olympics in Calgary, Alberta, Eddie and Bronson employ various unorthodox methods to condition and refine Eddie's form, and he successfully completes the 40m hill.

text: To qualify for the British Olympic division in ski jumping, Eddie only needs to complete a jump from a 70-metre (230 ft) hill in order to qualify for the Winter Olympics. Not long after, he manages to land the jump successfully, with a distance of 34 metres (112 ft), thus winning a place on the British Olympic Team. However, the officials, in an effort to keep Eddie from sullying the Winter Games with his amateurish skillset, decide to change the rules and demand that he jump at least 61 metres (200 ft). Though discouraged, Eddie decides to continue training and performs on a circuit, his jumps increasing in length each time, but unable to meet the Olympic requirements. During a practice jump at the final event before the cutoff date for qualification, he lands a 61m jump exactly, but on his official jump, he falls and is disqualified. Eddie is devastated and resolves to return home to work with his father as a plasterer, but he receives a letter claiming that his qualifying practice jump is valid, and he happily tells Bronson that he's eligible to compete in the Winter Olympics. Bronson tries to dissuade him, promising that he will make a complete fool of himself and his country if he goes, but Eddie is undeterred, noting that competing in the Olympics was always enough for him.

text: Upon arriving in Calgary, he receives instant scorn from the other British athletes, who get him drunk and nearly provoke him into fighting after he is subsequently absent from the opening ceremonies. Despite finishing last in the 70m jump with 60.5 metres (198 ft), Eddie sets a British record. His triumphant celebrations win the audience over, and the media embrace him as Eddie "The Eagle". Over the phone, Bronson criticises Edwards for not taking the sport seriously. Edwards publicly apologizes to the press for his antics, and wanting to ensure he does not leave the games as little more than a novelty, he enters the 90-metre (300 ft) jump, which he had never attempted before. Bronson decides to travel to the games and support him. After an encouraging conversation with his idol Matti "The Flying Finn" Nykänen on the lift to the top of the hill, Eddie barely manages to land a 71.5-metre (235 ft) jump. Once again, he scores last in the event, but is nonetheless cheered by the audience as well as millions around the world, which includes a playful salute in the closing speech of the President of the Organising Committee for the Olympic Games, Frank King. British Olympic officials grudgingly accept him.

text: Warren Sharp reconciles with Bronson, who was present, and Edwards returns home a national hero to the cheers of his fans at the airport, his mother rushes to him embracing him. And as Eddie looks to his father, he reveals a jumper declaring his support before then embracing Eddie as well.

text: Cast[edit]

text: Taron Egerton as Eddie "The Eagle" Edwards

text:
Tom Costello as 10-year-old Eddie Edwards
Jack Costello as 15-year-old Eddie Edwards

text:
Hugh Jackman as Bronson Peary[5]
Christopher Walken as Warren Sharp[6]
Iris Berben as Petra
Mark Benton[7] as Richmond, a BOA official
Keith Allen as Terry
Jo Hartley as Janette Edwards
Ania Sowinski as Clarrie
Tim McInnerny as Dustin Target
Edvin Endre as Matti "The Flying Finn" Nykänen
Marc Benjamin as Lars Holbin
Jim Broadbent as a BBC commentator
Daniel Ings as Zach
Rune Temte as Bjørn, a Norwegian coach

text: Production[edit]

text: Development[edit]

text: Eddie the Eagle is a co-production of Marv Films (UK), Studio Babelsberg (Germany) and Saville Productions (US).[8][9][10] In March 2015, it was announced that 20th Century Fox had acquired the film, with Taron Egerton[11] and Hugh Jackman starring and Dexter Fletcher directing, from a screenplay by Sean Macaulay and Simon Kelton.[12][13][14] Egerton would portray Eddie "The Eagle" Edwards, while Jackman would portray Bronson Peary, his coach; Jackman's character was confirmed as fictional by Eddie Edwards.[15][16] It was also announced that Matthew Vaughn, who produced Kingsman: The Secret Service, would reunite with the studio, serving as a producer on the film, while Adam Bohling, David Reid, Rupert Maconick and Valerie Van Galde would also serve as producers.[12] That same month, it was announced that Christopher Walken had joined the film, portraying the role of Jackman's character's mentor.[6]

text: The film received funds of €2.2 million, from the German Federal Film Fund (DFFF).[17]

text: Filming[edit]

text: Principal photography took place in Oberstdorf and Garmisch-Partenkirchen in Bavaria, in Seefeld in Tirol, at the Pinewood Studios and in London from 9 March to 3 May 2015.[18] Dry slope scenes were filmed at a dry ski slope in Bracknell, Berkshire, UK.

text: Release[edit]

text: In March 2015, it was announced 20th Century Fox would distribute the film in the United States of America. The studio set 29 April 2016 for the release of the film.[12] That same month, it was announced that Lionsgate had acquired United Kingdom distribution rights to the film, with a spring 2016 release planned.[19] In October 2015, Lionsgate set a release date for the film for 1 April 2016.[20] The date was then moved forward to 28 March 2016. The same month, it was announced that the film had delayed to 26 February in the United States.[21] The film had its world premiere at the 2016 Sundance Film Festival as a "Surprise Screening" on 26 January 2016.[4]. The subsequent London premiere took place on 17 March, 2016.[22]

text: Soundtrack[edit]

text: "Fly: Songs Inspired by the Film 'Eddie the Eagle,'" curated by Gary Barlow, was release on 1 April 2016 featuring new songs from Tony Hadley, Marc Almond, Holly Johnson, Paul Young, Kim Wilde, Andy Bell, Midge Ure, Nik Kershaw, ABC, Deacon Blue, Van Halen, Go West, Howard Jones, OMD and Heaven 17.

text: Reception[edit]

text: Box office[edit]

text: Eddie the Eagle grossed a worldwide total of $46.1 million. In the UK, it grossed $12.8m making it the highest grossing British film released in the UK in 2016.[3]

text: Critical response[edit]

text: On Rotten Tomatoes, the film has a rating of 80% based on 167 reviews, with an average rating of 6.5/10. The site's consensus reads, "Eddie the Eagle's amiable sweetness can't disguise its story's many inspirational clichés – but for many viewers, it will be more than enough to make up for them."[23] On Metacritic the film has a score of 54 out of 100, based on 34 critics, indicating "mixed or average reviews".[24] Audiences polled by CinemaScore gave the film an average grade of "A" on an A+ to F scale.[25]

text: Alonso Duralde of TheWrap wrote, "Eddie the Eagle is designed for audiences who will throw their weight behind the film’s schmaltz and sentimentality. Anyone unwilling to commit to the movie’s shamelessness will feel like they’ve hit the ground headfirst."[26] KenyaBuzz called it a must-watch saying it is "positively impetuous and unbearably affectionate."[27] A sportswriter who attended the events in which the real Eddie competed, wrote "three generations of my family loved this film. You can't believe most of it, but you can believe in it. That's a subtle but important difference."[28]

text: Accolades[edit]

text:
Award
Date of ceremony
Category
Recipient(s)
Result
Ref(s)

Empire Awards
March 19, 2017
Best British Film
Eddie the Eagle
Nominated
[29]

Golden Tomato Awards
January 12, 2017
Best British Movie 2016
Eddie the Eagle
5th Place
[30]

Golden Trailer Awards
May 4, 2016
Best Animation Family
"Sport"
Nominated
[31]

Teen Choice Awards
July 31, 2016
Choice Movie Actor: Drama
Taron Egerton
Nominated
[32]

tag: table