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10 relations: Biometrika, Cumulative distribution function, Data set, Jean D. Gibbons, Median, Probability plot, Q–Q plot, Quantile, Skewness, Variance-stabilizing transformation.
Biometrika
Biometrika is a peer-reviewed scientific journal published by Oxford University Press for the Biometrika Trust.
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Cumulative distribution function
In probability theory and statistics, the cumulative distribution function (CDF, also cumulative density function) 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. In the case of a continuous distribution, it gives the area under the probability density function from minus infinity to x. Cumulative distribution functions are also used to specify the distribution of multivariate random variables.
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Data set
A data set (or dataset) is a collection of data.
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Jean D. Gibbons
Jean Dickinson Gibbons (née Dickinson, born 1938) is an American statistician, an expert in nonparametric statistics and an author of books on statistics.
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Median
The median is the value separating the higher half of a data sample, a population, or a probability distribution, from the lower half.
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Probability plot
In statistics, a probability plot is a graphical technique for comparing two data sets, either two sets of empirical observations, one empirical set against a theoretical set, or (more rarely) two theoretical sets against each other.
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Q–Q plot
In statistics, a Q–Q (quantile-quantile) plot is a probability plot, which is a graphical method for comparing two probability distributions by plotting their quantiles against each other.
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Quantile
In statistics and probability quantiles are cut points dividing the range of a probability distribution into contiguous intervals with equal probabilities, or dividing the observations in a sample in the same way.
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Skewness
In probability theory and statistics, skewness is a measure of the asymmetry of the probability distribution of a real-valued random variable about its mean.
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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.
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