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Statistics is a mathematical science pertaining to the collection, analysis, interpretation or explanation, and presentation of data. It is applicable to a wide variety of academic disciplines, from the natural and social sciences to the humanities, government and business.

Statistical methods are used to summarize and describe a collection of data; this is called descriptive statistics. In addition, patterns in the data may be modeled in a way that accounts for randomness and uncertainty in the observations, and then used to draw inferences about the process or population being studied; this is called inferential statistics.

Statistics arose no later than the 18th century from the need of states to collect data on their people and economies, in order to administer them. The meaning broadened in the early 19th century to include the collection and analysis of data in general.

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Datasets with various correlation coefficients

A correlation, (often measured as a correlation coefficient), indicates the strength and direction of a linear relationship between two random variables. In general statistical usage, correlation or co-relation refers to the departure of two variables from independence. In this broad sense there are several coefficients, measuring the degree of correlation, adapted to the nature of data. A number of different coefficients are used for different situations. The best known is the Pearson product-moment correlation coefficient, which is obtained by dividing the covariance of the two variables by the product of their standard deviations. Despite its name, it was first introduced by Francis Galton.


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Karl Pearson

Karl Pearson FRS (1857–1936) established the discipline of mathematical statistics. In 1911 he founded the world's first university statistics department at University College London. Pearson's work was all-embracing in the wide application and development of mathematical statistics, and encompassed the fields of biology, epidemiology, anthropometry, medicine and social history. Pearson's thinking underpins many of the 'classical' statistical methods which are still in common use today, including linear regression, correlation and the classification of probability distributions. He gave his name to Pearson's correlation coefficient and Pearson's chi-square test.


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The Statistics WikiProject is the center for improving statistics articles on Wikipedia. If you would like to participate, please visit the project page, where you can join the project and see a list of open tasks.

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A polar area diagram
Credit: Florence Nightingale

A polar area diagram by Florence Nightingale. The polar area diagram is similar to a pie chart, except that the sectors are each of an equal angle and differ rather in how far each sector extends from the centre of the circle, enabling multiple comparisons on one diagram. This "DIAGRAM of the CAUSES of MORTALITY in the ARMY in the EAST" was published in Notes on Matters Affecting the Health, Efficiency, and Hospital Administration of the British Army and sent to Queen Victoria in 1858. It shows the number of deaths due to preventable diseases (blue), wounds (red), and other causes (black).


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