Changes

==Origin==

==Origin==

German ''Statistik'' [[study]] of [[political]] [[facts]] and figures, from New Latin ''statisticus'' of politics, from Latin ''status'' [[state]]

German ''Statistik'' [[study]] of [[political]] [[facts]] and figures, from New Latin ''statisticus'' of politics, from Latin ''status'' [[state]]

*[http://en.wikipedia.org/wiki/18th_century 1770]

*[https://en.wikipedia.org/wiki/18th_century 1770]

==Definition==

==Definition==

*1:  a branch of [[mathematics]] dealing with the collection, [[analysis]], [[interpretation]], and presentation of masses of numerical [[data]]

*1:  a branch of [[mathematics]] dealing with the collection, [[analysis]], [[interpretation]], and presentation of masses of numerical [[data]]

'''Statistics''' is described as a [[mathematical]] body of [[science]] that pertains to the collection, analysis, interpretation or explanation, and presentation of [[data]], or as a branch of mathematics concerned with collecting and interpreting data. Because of its [[empirical]] roots and its focus on [[applications]], statistics is typically considered a distinct mathematical science rather than as a branch of mathematics. Some tasks a statistician may involve are less mathematical; for example, ensuring that data collection is undertaken in a way that produces valid [[conclusions]], coding data, or reporting results in ways [[comprehensible]] to those who must use them.

'''Statistics''' is described as a [[mathematical]] body of [[science]] that pertains to the collection, analysis, interpretation or explanation, and presentation of [[data]], or as a branch of mathematics concerned with collecting and interpreting data. Because of its [[empirical]] roots and its focus on [[applications]], statistics is typically considered a distinct mathematical science rather than as a branch of mathematics. Some tasks a statistician may involve are less mathematical; for example, ensuring that data collection is undertaken in a way that produces valid [[conclusions]], coding data, or reporting results in ways [[comprehensible]] to those who must use them.

Statisticians improve data [[quality]] by developing specific [[experiment]] designs and survey samples. Statistics itself also provides tools for [[prediction]] and [[forecasting]] the use of data through [http://en.wikipedia.org/wiki/Statistical_model statistical models]. Statistics is applicable to a wide variety of [http://en.wikipedia.org/wiki/Academic_discipline academic disciplines], including natural and [[social sciences]], [[government]], and [[business]]. Statistical consultants can help [[organizations]] and companies that don't have in-house expertise relevant to their particular questions.

Statisticians improve data [[quality]] by developing specific [[experiment]] designs and survey samples. Statistics itself also provides tools for [[prediction]] and [[forecasting]] the use of data through [https://en.wikipedia.org/wiki/Statistical_model statistical models]. Statistics is applicable to a wide variety of [https://en.wikipedia.org/wiki/Academic_discipline academic disciplines], including natural and [[social sciences]], [[government]], and [[business]]. Statistical consultants can help [[organizations]] and companies that don't have in-house expertise relevant to their particular questions.

Statistical methods can summarize or describe a collection of [[data]]. This is called ''[http://en.wikipedia.org/wiki/Descriptive_statistics descriptive statistics]''. This is particularly useful in communicating the results of [[experiments]] and [[research]]. In addition, data patterns may be modeled in a way that accounts for [[random]]ness and [[uncertainty]] in the observations.

Statistical methods can summarize or describe a collection of [[data]]. This is called ''[https://en.wikipedia.org/wiki/Descriptive_statistics descriptive statistics]''. This is particularly useful in communicating the results of [[experiments]] and [[research]]. In addition, data patterns may be modeled in a way that accounts for [[random]]ness and [[uncertainty]] in the observations.

These models can be used to draw [[inferences]] about the [[process]] or [[population]] under study—a practice called [http://en.wikipedia.org/wiki/Inferential_statistics inferential statistics]. Inference is a vital element of scientific advance, since it provides a way to draw conclusions from data that are subject to random variation. To prove the [[propositions]] being investigated further, the conclusions are tested as well, as part of the [[scientific method]]. Descriptive statistics and analysis of the new data tend to provide more information as to the [[truth]] of the proposition.

These models can be used to draw [[inferences]] about the [[process]] or [[population]] under study—a practice called [https://en.wikipedia.org/wiki/Inferential_statistics inferential statistics]. Inference is a vital element of scientific advance, since it provides a way to draw conclusions from data that are subject to random variation. To prove the [[propositions]] being investigated further, the conclusions are tested as well, as part of the [[scientific method]]. Descriptive statistics and analysis of the new data tend to provide more information as to the [[truth]] of the proposition.

"Applied statistics" comprises descriptive statistics and the application of inferential statistics. Theoretical statistics concerns both the logical [[arguments]] underlying [[justification]] of approaches to [http://en.wikipedia.org/wiki/Statistical_inference statistical inference], as well encompassing ''[http://en.wikipedia.org/wiki/Mathematical_statistics mathematical statistics]''. Mathematical statistics includes not only the [[manipulation]] of [[probability]] distributions necessary for deriving results related to methods of estimation and inference, but also various aspects of ''[http://en.wikipedia.org/wiki/Computational_statistics computational statistics]'' and the design of experiments.

"Applied statistics" comprises descriptive statistics and the application of inferential statistics. Theoretical statistics concerns both the logical [[arguments]] underlying [[justification]] of approaches to [https://en.wikipedia.org/wiki/Statistical_inference statistical inference], as well encompassing ''[https://en.wikipedia.org/wiki/Mathematical_statistics mathematical statistics]''. Mathematical statistics includes not only the [[manipulation]] of [[probability]] distributions necessary for deriving results related to methods of estimation and inference, but also various aspects of ''[https://en.wikipedia.org/wiki/Computational_statistics computational statistics]'' and the design of experiments.

Statistics is closely related to [http://en.wikipedia.org/wiki/Probability_theory probability theory], with which it is often grouped. The [[difference]] is, roughly, that probability theory starts from the given [[parameters]] of a total population to deduce probabilities that pertain to samples. Statistical inference, however, moves in the opposite direction—inductively inferring from samples to the parameters of a larger or total population. Statistics has many ties to [http://en.wikipedia.org/wiki/Machine_learning machine learning] and [http://en.wikipedia.org/wiki/Data_mining data mining].[http://en.wikipedia.org/wiki/Statistics]

Statistics is closely related to [https://en.wikipedia.org/wiki/Probability_theory probability theory], with which it is often grouped. The [[difference]] is, roughly, that probability theory starts from the given [[parameters]] of a total population to deduce probabilities that pertain to samples. Statistical inference, however, moves in the opposite direction—inductively inferring from samples to the parameters of a larger or total population. Statistics has many ties to [https://en.wikipedia.org/wiki/Machine_learning machine learning] and [https://en.wikipedia.org/wiki/Data_mining data mining].[https://en.wikipedia.org/wiki/Statistics]

[[Category: General Reference]]

[[Category: General Reference]]

[[Category: Statistics]]

[[Category: Statistics]]