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P–P Plot
In statistics, a P–P plot (probability–probability plot or percent–percent plot or P value plot) is a probability plot for assessing how closely two data sets agree, or for assessing how closely a dataset fits a particular model. It works by plotting the two cumulative distribution functions against each other; if they are similar, the data will appear to be nearly a straight line. This behavior is similar to that of the more widely used Q–Q plot, with which it is often confused. Definition A P–P plot plots two cumulative distribution functions (cdfs) against each other: given two probability distributions, with cdfs "''F''" and "''G''", it plots (F(z),G(z)) as ''z'' ranges from -\infty to \infty. As a cdf has range ,1 the domain of this parametric graph is (-\infty,\infty) and the range is the unit square ,1times ,1 Thus for input ''z'' the output is the pair of numbers giving what ''percentage'' of ''f'' and what ''percentage'' of ''g'' fall at or below ''z.'' ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Data Set
A data set (or dataset) is a collection of data. In the case of tabular data, a data set corresponds to one or more table (database), database tables, where every column (database), column of a table represents a particular Variable (computer science), variable, and each row (database), row corresponds to a given Record (computer science), record of the data set in question. The data set lists values for each of the variables, such as for example height and weight of an object, for each member of the data set. Data sets can also consist of a collection of documents or files. In the open data discipline, a dataset is a unit used to measure the amount of information released in a public open data repository. The European data.europa.eu portal aggregates more than a million data sets. Properties Several characteristics define a data set's structure and properties. These include the number and types of the attributes or variables, and various statistical measures applicable to the ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Cumulative Distribution Function
In probability theory and statistics, the cumulative distribution function (CDF) of a real-valued random variable X, or just distribution function of X, evaluated at x, is the probability that X will take a value less than or equal to x. Every probability distribution Support (measure theory), supported on the real numbers, discrete or "mixed" as well as Continuous variable, continuous, is uniquely identified by a right-continuous Monotonic function, monotone increasing function (a càdlàg function) F \colon \mathbb R \rightarrow [0,1] satisfying \lim_F(x)=0 and \lim_F(x)=1. In the case of a scalar continuous distribution, it gives the area under the probability density function from negative infinity to x. Cumulative distribution functions are also used to specify the distribution of multivariate random variables. Definition The cumulative distribution function of a real-valued random variable X is the function given by where the right-hand side represents the probability ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Q–Q Plot
In statistics, a Q–Q plot (quantile–quantile plot) is a probability plot, a List of graphical methods, graphical method for comparing two probability distributions by plotting their ''quantiles'' against each other. A point on the plot corresponds to one of the quantiles of the second distribution (-coordinate) plotted against the same quantile of the first distribution (-coordinate). This defines a parametric plot, parametric curve where the parameter is the index of the quantile interval. If the two distributions being compared are similar, the points in the Q–Q plot will approximately lie on the identity line . If the distributions are linearly related, the points in the Q–Q plot will approximately lie on a line, but not necessarily on the line . Q–Q plots can also be used as a graphical means of estimating parameters in a location-scale family of distributions. A Q–Q plot is used to compare the shapes of distributions, providing a graphical view of how pro ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
CRC Press
The CRC Press, LLC is an American publishing group that specializes in producing technical books. Many of their books relate to engineering, science and mathematics. Their scope also includes books on business, forensics and information technology. CRC Press is now a division of Taylor & Francis, itself a subsidiary of Informa. History The CRC Press was founded as the Chemical Rubber Company (CRC) in 1903 by brothers Arthur, Leo and Emanuel Friedman in Cleveland, Ohio, based on an earlier enterprise by Arthur, who had begun selling rubber laboratory aprons in 1900. The company gradually expanded to include sales of laboratory equipment to chemist A chemist (from Greek ''chēm(ía)'' alchemy; replacing ''chymist'' from Medieval Latin ''alchemist'') is a graduated scientist trained in the study of chemistry, or an officially enrolled student in the field. Chemists study the composition of ...s. In 1913 the CRC offered a short (116-page) manual called the ''Rubber Handboo ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Median
The median of a set of numbers is the value separating the higher half from the lower half of a Sample (statistics), data sample, a statistical population, population, or a probability distribution. For a data set, it may be thought of as the “middle" value. The basic feature of the median in describing data compared to the Arithmetic mean, mean (often simply described as the "average") is that it is not Skewness, skewed by a small proportion of extremely large or small values, and therefore provides a better representation of the center. Median income, for example, may be a better way to describe the center of the income distribution because increases in the largest incomes alone have no effect on the median. For this reason, the median is of central importance in robust statistics. Median is a 2-quantile; it is the value that partitions a set into two equal parts. Finite set of numbers The median of a finite list of numbers is the "middle" number, when those numbers are liste ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Quantile
In statistics and probability, quantiles are cut points dividing the range of a probability distribution into continuous intervals with equal probabilities or dividing the observations in a sample in the same way. There is one fewer quantile than the number of groups created. Common quantiles have special names, such as '' quartiles'' (four groups), '' deciles'' (ten groups), and '' percentiles'' (100 groups). The groups created are termed halves, thirds, quarters, etc., though sometimes the terms for the quantile are used for the groups created, rather than for the cut points. -quantiles are values that partition a finite set of values into subsets of (nearly) equal sizes. There are partitions of the -quantiles, one for each integer satisfying . In some cases the value of a quantile may not be uniquely determined, as can be the case for the median (2-quantile) of a uniform probability distribution on a set of even size. Quantiles can also be applied to continuous di ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Biometrika
''Biometrika'' is a peer-reviewed scientific journal published by Oxford University Press for the Biometrika Trust. The editor-in-chief is Paul Fearnhead (Lancaster University). The principal focus of this journal is theoretical statistics. It was established in 1901 and originally appeared quarterly. It changed to three issues per year in 1977 but returned to quarterly publication in 1992. History ''Biometrika'' was established in 1901 by Francis Galton, Karl Pearson, and Raphael Weldon to promote the study of biometrics. The history of ''Biometrika'' is covered by Cox (2001). The name of the journal was chosen by Pearson, but Francis Edgeworth insisted that it be spelt with a "k" and not a "c". Since the 1930s, it has been a journal for statistical theory and methodology. Galton's role in the journal was essentially that of a patron and the journal was run by Pearson and Weldon and after Weldon's death in 1906 by Pearson alone until he died in 1936. In the early days, the Ameri ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Galen Shorack
Galen Richard Shorack (born 14 May 1939) is an American statistician. Shorack completed his bachelor's and master's degrees in mathematics at the University of Oregon in 1960 and 1962, respectively. He then obtained a Ph.D in statistics from Stanford University in 1965, authoring the doctoral dissertation ''Nonparametric Tests and Estimation of Scale in the Two Sample Problem'' under the direction of Lincoln E. Moses. Shorack joined the University of Washington The University of Washington (UW and informally U-Dub or U Dub) is a public research university in Seattle, Washington, United States. Founded in 1861, the University of Washington is one of the oldest universities on the West Coast of the Uni ... faculty upon earning his doctorate in 1965, and remained on the faculty until 2015, when he retired and was granted emeritus status. Shorack was elected to fellowship of the Institute of Mathematical Statistics in 1974. Books * Review * ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Jon A
Jon is a shortened form of the common given name Jonathan, derived from "YHWH has given". The name is spelled Jón in Iceland and on the Faroe Islands. In the Nordic countries, it is derived from Johannes. Notable people * Jon Aaraas (born 1986), Norwegian ski jumper *Jon Abbate (born 1985), American gridiron football player * Jon Abbott, American media executive * Jon Aberasturi (born 1989), Basque bicycle racer * Jon Ramon Aboitiz (1948–2018), Filipino businessman *Jon Abrahams (born 1977), American actor *Jon Abrahamsen (born 1951), Norwegian footballer *Jon Ackerson, American lawyer and politician * Jon Adams, American folk musician *Jon Adkins (born 1977), American baseball player *Jon Agee (born 1960), American writer and illustrator *Jon Agirre (born 1997), Spanish cyclist * Jon E. Ahlquist (1944–2020), American molecular biologist and ornithologist *Jon Akass (1933–1990), British journalist *Jon Åker (1927–2013), Norwegian hospital director * Jon Akin (born 1977) ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Variance-stabilizing Transformation
In applied statistics, a variance-stabilizing transformation is a data transformation that is specifically chosen either to simplify considerations in graphical exploratory data analysis or to allow the application of simple regression-based or analysis of variance techniques. Overview The aim behind the choice of a variance-stabilizing transformation is to find a simple function ''ƒ'' to apply to values ''x'' in a data set to create new values such that the variability of the values ''y'' is not related to their mean value. For example, suppose that the values x are realizations from different Poisson distributions: i.e. the distributions each have different mean values ''μ''. Then, because for the Poisson distribution the variance is identical to the mean, the variance varies with the mean. However, if the simple variance-stabilizing transformation :y=\sqrt \, is applied, the sampling variance associated with observation will be nearly constant: see Anscombe transform for ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Probability Plot (other)
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Probability plot, a graphical technique for comparing two data sets, may refer to: *P–P plot, "Probability-Probability" or "Percent-Percent" plot *Q–Q plot, "Quantile-Quantile" plot *Normal probability plot, a Q–Q plot against the standard normal distribution See also *Probability plot correlation coefficient *Probability plot correlation coefficient plot The probability plot correlation coefficient (PPCC) plot is a graphical technique for identifying the shape parameter for a distributional family that best describes the data set. This technique is appropriate for families, such as the Weibull, th ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
