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The theory of statistics provides a basis for the whole range of techniques, in both study design and data analysis, that are used within applications of statistics. [1] [2] The theory covers approaches to statistical-decision problems and to statistical inference, and the actions and deductions that satisfy the basic principles stated for these different approaches.
Statistics is the theory and application of mathematics to the scientific method including hypothesis generation, experimental design, sampling, data collection, data summarization, estimation, prediction and inference from those results to the population from which the experimental sample was drawn.
Statistics subsequently branched out into various directions, including decision theory, Bayesian statistics, exploratory data analysis, robust statistics, and non-parametric statistics. Neyman-Pearson hypothesis testing made significant contributions to decision theory, which is widely employed, particularly in statistical quality control.
Illustration of the linear model in high-dimensions: a data set consists of a response vector and a design matrix with .Our goal is to estimate the unknown vector = (, …,) of regression coefficients where is often assumed to be sparse, in the sense that the cardinality of the set := {:} is small by comparison with .
In statistics, the generalized Pareto distribution (GPD) is a family of continuous probability distributions.It is often used to model the tails of another distribution. It is specified by three parameters: location , scale , and shape
Download as PDF; Printable version; In other projects Wikimedia Commons; Wikidata item; ... Asymptotic theory (statistics) (3 C, 18 P) B. Bayesian statistics (6 C, 93 ...