A detail about Father of Statistics

Born	17 February 1890 East Finchley, London, England
Died	29 July 1962 (aged 72) Adelaide, South Australia
Residence	England and Australia
Nationality	British
Fields	Statistics, Genetics, andEvolutionary biology
Institutions	Rothamsted Experimental Station University College London Cambridge University University of Adelaide, and CSIRO
Alma mater	University of Cambridge
Academic advisors	Sir James Jeans and F.J.M. Stratton
Doctoral students	C.R. Rao, D. J. Finney, and Walter Bodmer
Known for	Fisher's fundamental theorem Maximum likelihood Fisher information Analysis of variance The Fisher–Kolmogorov equation Fisher's geometric model Coining the term "null hypothesis" Fiducial inference Fisher's exact test Fisher's principle Fisherian runaway The F-distribution
Influences	Leonard Darwin
Influenced	Joseph Oscar Irwin A. W. F. Edwards Georg Rasch W. D. Hamilton Oscar Kempthorne, Richard Dawkins
Notable awards	Royal Medal (1938) Guy Medal in Gold (1946) Copley Medal (1955) Linnean Society of London'sDarwin–Wallace Medal (1958).
Notes: He was the father-in-law of George E. P. Box.

Sir Ronald Aylmer Fisher FRS (17 February 1890 – 29 July 1962) was an English statistician, evolutionary biologist, geneticist, andeugenicist. Fisher is known as one of the chief architects of the neo-Darwinian synthesis, and for his important contributions to statistics, including the Analysis of Variance (ANOVA), method of maximum likelihood, fiducial inference, and the derivation of various sampling distributions. Anders Hald called him "a genius who almost single-handedly created the foundations for modern statistical science",^[1] whileRichard Dawkins named him "the greatest biologist since Darwin".^[2]

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Double exponential distribution

Double Exponential Distribution Probability Density Function The general formula for the probability density function of the double exponential distribution is where is the location parameter and is the scale parameter . The case where = 0 and = 1 is called the standard double exponential distribution . The equation for the standard double exponential distribution is Since the general form of probability functions can be expressed in terms of the standard distribution , all subsequent formulas in this section are given for the standard form of the function. The following is the plot of the double exponential probability density function. Cumulative Distribution Function The formula for the cumulative distribution function of the double exponential distribution is The following is the plot of the double exponential cumulative distribution function. Percent Point Function The formula for the percent point function of the double exponential distribution

Runs Test for Detecting Non-randomness

Runs Test for Detecting Non-randomness Purpose: Detect Non-Randomness The runs test ( Bradley, 1968 ) can be used to decide if a data set is from a random process. A run is defined as a series of increasing values or a series of decreasing values. The number of increasing, or decreasing, values is the length of the run. In a random data set, the probability that the ( I +1)th value is larger or smaller than the I th value follows a binomial distribution , which forms the basis of the runs test. Typical Analysis and Test Statistics The first step in the runs test is to count the number of runs in the data sequence. There are several ways to define runs in the literature, however, in all cases the formulation must produce a dichotomous sequence of values. For example, a series of 20 coin tosses might produce the f

Basics of Sampling Techniques

Population A population is a group of individuals(or)aggregate of objects under study.It is also known as universe. The population is divided by (i)finite population (ii)infinite population, (iii) hypothetical population, subject to a statistical study . A population includes each element from the set of observations that can be made. (i) Finite population : A population is called finite if it is possible to count its individuals. It may also be called a countable population. The number of vehicles crossing a bridge every day, (ii) Infinite population : Sometimes it is not possible to count the units contained in the population. Such a population is called infinite or uncountable. ex, The number of germs in the body of a patient of malaria is perhaps something which is uncountable (iii) Hypothetical population : Statistical population which has no real existence but is imagined to be generated by repetitions of events of a certain typ

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