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Lady Tasting Tea
In the design of experiments in statistics, the lady tasting tea is a randomized experiment devised by Ronald Fisher and reported in his book ''The Design of Experiments'' (1935). The experiment is the original exposition of Fisher's notion of a null hypothesis, which is "never proved or established, but is possibly disproved, in the course of experimentation".OED quote: 1935 R. A. Fisher, ''The Design of Experiments'' ii. 19, "We may speak of this hypothesis as the 'null hypothesis' ..the null hypothesis is never proved or established, but is possibly disproved, in the course of experimentation." The lady in question (Muriel Bristol) claimed to be able to tell whether the tea or the milk was added first to a cup. Fisher proposed to give her eight cups, four of each variety, in random order. One could then ask what the probability was for her getting the specific number of cups she identified correct, but just by chance. Fisher's description is less than 10 pages in length and ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Nice Cup Of Tea
Nice ( , ; Niçard: , classical norm, or , nonstandard, ; it, Nizza ; lij, Nissa; grc, Νίκαια; la, Nicaea) is the prefecture of the Alpes-Maritimes department in France. The Nice agglomeration extends far beyond the administrative city limits, with a population of nearly 1 millionDemographia: World Urban Areas , Demographia.com, April 2016 on an area of . Located on the , the southeastern coast of France on the , at the foot of the |
David Salsburg
David S. Salsburg (born 1931) is an author. His 2002 book ''The Lady Tasting Tea'', subtitled ''How Statistics Revolutionized Science in the Twentieth Century'', provides a layman's overview of important developments in the field of statistics in the late 19th and early 20th century, particularly in the areas of Design of experiments, experiment design, the study of Probability distribution, random distributions, and the careers of major researchers in the field such as Ronald Fisher, Karl Pearson, and Jerzy Neyman. Salsburg is a retired pharmaceutical company statistician (having been a senior research fellow at Pfizer's central research department until 1995) who has taught at Harvard, Yale, Connecticut College, the University of Connecticut, the University of Pennsylvania, Rhode Island College, and Trinity College (Connecticut), Trinity College and has been a Fellow of the American Statistical Association since 1978. In 1994, Salsburg was awarded the ''Career Achievement Award of ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Design Of Experiments
The design of experiments (DOE, DOX, or experimental design) is the design of any task that aims to describe and explain the variation of information under conditions that are hypothesized to reflect the variation. The term is generally associated with experiments in which the design introduces conditions that directly affect the variation, but may also refer to the design of quasi-experiments, in which natural conditions that influence the variation are selected for observation. In its simplest form, an experiment aims at predicting the outcome by introducing a change of the preconditions, which is represented by one or more independent variables, also referred to as "input variables" or "predictor variables." The change in one or more independent variables is generally hypothesized to result in a change in one or more dependent variables, also referred to as "output variables" or "response variables." The experimental design may also identify control variables that must be h ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
How Statistics Revolutionized Science In The Twentieth Century
How may refer to: * How (greeting), a word used in some misrepresentations of Native American/First Nations speech * How, an interrogative word in English grammar Art and entertainment Literature * ''How'' (book), a 2007 book by Dov Seidman * ''HOW'' (magazine), a magazine for graphic designers * H.O.W. Journal, an American art and literary journal Music * "How", a song by The Cranberries from ''Everybody Else Is Doing It, So Why Can't We?'' * "How", a song by Maroon 5 from ''Hands All Over'' * "How", a song by Regina Spektor from ''What We Saw from the Cheap Seats'' * "How", a song by Daughter from ''Not to Disappear'' * "How?" (song), by John Lennon Other media * HOW (graffiti artist), Raoul Perre, New York graffiti muralist * ''How'' (TV series), a British children's television show * ''How'' (video game), a platform game People * How (surname) * HOW (graffiti artist), Raoul Perre, New York graffiti muralist Places * How, Cumbria, England * How, Wisconsin, Un ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Jayanta Kumar Ghosh
Jayanta Kumar Ghosh (Bengali: জয়ন্ত কুমার ঘোষ, 23 May 1937 – 30 September 2017) was an Indian statistician, an emeritus professor at Indian Statistical Institute and a professor of statistics at Purdue University. Education He obtained a B.S. from Presidency College, then affiliated with the University of Calcutta, and subsequently a M.A. and a Ph.D. from the University of Calcutta under the supervision of H. K. Nandi. He started his research career in the early 1960s, studying sequential analysis as a graduate student in the department of statistics at the University of Calcutta. Research Among his best-known discoveries are the Bahadur–Ghosh–Kiefer representation (with R. R. Bahadur and Jack Kiefer) and the Ghosh–Pratt identity along with John W. Pratt. His research contributions fall within the fields of: * Bayesian inference * Asymptotics * Modeling and model selection * High dimensional data analysis * Nonparametric regress ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Debabrata Basu
Debabrata Basu (5 July 1924 – 24 March 2001) was an Indian statistician who made fundamental contributions to the foundations of statistics. Basu invented simple examples that displayed some difficulties of likelihood-based statistics and frequentist statistics; Basu's paradoxes were especially important in the development of survey sampling. In statistical theory, Basu's theorem established the independence of a complete sufficient statistic and an ancillary statistic. Page i in Basu was associated with the Indian Statistical Institute in India, and Florida State University in the United States.Page i in "Preface" to IMS festschrift. Biography Debabrata Basu was born in Dacca, Bengal, unpartitioned India, now Dhaka, Bangladesh. His father, N. M. Basu, was a mathematician specialising in number theory. Young Basu studied mathematics at Dacca University. He took a course in statistics as part of the under-graduate honours programme in Mathematics but his ambition wa ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Randomization Test
In statistics, resampling is the creation of new samples based on one observed sample. Resampling methods are: # Permutation tests (also re-randomization tests) # Bootstrapping # Cross validation Permutation tests Permutation tests rely on resampling the original data assuming the null hypothesis. Based on the resampled data it can be concluded how likely the original data is to occur under the null hypothesis. Bootstrap Bootstrapping is a statistical method for estimating the sampling distribution of an estimator by sampling with replacement from the original sample, most often with the purpose of deriving robust estimates of standard errors and confidence intervals of a population parameter like a mean, median, proportion, odds ratio, correlation coefficient or regression coefficient. It has been called the plug-in principle,Logan, J. David and Wolesensky, Willian R. Mathematical methods in biology. Pure and Applied Mathematics: a Wiley-interscience Series of Texts, M ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Random Assignment
Random assignment or random placement is an experimental technique for assigning human participants or animal subjects to different groups in an experiment (e.g., a treatment group versus a control group) using randomization, such as by a chance procedure (e.g., flipping a coin) or a random number generator. This ensures that each participant or subject has an equal chance of being placed in any group. Random assignment of participants helps to ensure that any differences between and within the groups are not systematic at the outset of the experiment. Thus, any differences between groups recorded at the end of the experiment can be more confidently attributed to the experimental procedures or treatment. Random assignment, blinding, and controlling are key aspects of the design of experiments because they help ensure that the results are not spurious or deceptive via confounding. This is why randomized controlled trials are vital in clinical research, especially ones that ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Permutation Test
A permutation test (also called re-randomization test) is an exact statistical hypothesis test making use of the proof by contradiction. A permutation test involves two or more samples. The null hypothesis is that all samples come from the same distribution H_0: F=G. Under the null hypothesis, the distribution of the test statistic is obtained by calculating all possible values of the test statistic under possible rearrangements of the observed data. Permutation tests are, therefore, a form of resampling. Permutation tests can be understood as surrogate data testing where the surrogate data under the null hypothesis are obtained through permutations of the original data. In other words, the method by which treatments are allocated to subjects in an experimental design is mirrored in the analysis of that design. If the labels are exchangeable under the null hypothesis, then the resulting tests yield exact significance levels; see also exchangeability. Confidence intervals can then ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Hypergeometric Distribution
In probability theory and statistics, the hypergeometric distribution is a discrete probability distribution that describes the probability of k successes (random draws for which the object drawn has a specified feature) in n draws, ''without'' replacement, from a finite population of size N that contains exactly K objects with that feature, wherein each draw is either a success or a failure. In contrast, the binomial distribution describes the probability of k successes in n draws ''with'' replacement. Definitions Probability mass function The following conditions characterize the hypergeometric distribution: * The result of each draw (the elements of the population being sampled) can be classified into one of two mutually exclusive categories (e.g. Pass/Fail or Employed/Unemployed). * The probability of a success changes on each draw, as each draw decreases the population (''sampling without replacement'' from a finite population). A random variable X follows the hyperg ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Deb Basu
Debabrata Basu (5 July 1924 – 24 March 2001) was an Indian statistician who made fundamental contributions to the foundations of statistics. Basu invented simple examples that displayed some difficulties of likelihood-based statistics and frequentist statistics; Basu's paradoxes were especially important in the development of survey sampling. In statistical theory, Basu's theorem established the independence of a complete sufficient statistic and an ancillary statistic. Page i in Basu was associated with the Indian Statistical Institute in India, and Florida State University in the United States.Page i in "Preface" to IMS festschrift. Biography Debabrata Basu was born in Dacca, Bengal, unpartitioned India, now Dhaka, Bangladesh. His father, N. M. Basu, was a mathematician specialising in number theory. Young Basu studied mathematics at Dacca University. He took a course in statistics as part of the under-graduate honours programme in Mathematics but his ambition was to ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Randomization
Randomization is the process of making something random. Randomization is not haphazard; instead, a random process is a sequence of random variables describing a process whose outcomes do not follow a deterministic pattern, but follow an evolution described by probability distributions. For example, a random sample of individuals from a population refers to a sample where every individual has a known probability of being sampled. This would be contrasted with nonprobability sampling where arbitrary individuals are selected. In various contexts, randomization may involve: * generating a random permutation of a sequence (such as when shuffling cards); * selecting a random sample of a population (important in statistical sampling); * allocating experimental units via random assignment to a treatment or control condition; * generating random numbers (random number generation); or * transforming a data stream (such as when using a scrambler in telecommunications). Applications Randomi ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
