Introduction to measure and probability:
The authors believe that a proper treatment of probability theory requires an adequate background in the theory of finite measures in general spaces. The first part of their book sets out this material in a form that not only provides an introduction for intending specialists in measure theory but a...
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| 1. Verfasser: | |
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| Format: | Elektronisch E-Book |
| Sprache: | English |
| Veröffentlicht: |
Cambridge
Cambridge University Press
1966
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| Schlagworte: | |
| Online-Zugang: | BSB01 FHN01 Volltext |
| Zusammenfassung: | The authors believe that a proper treatment of probability theory requires an adequate background in the theory of finite measures in general spaces. The first part of their book sets out this material in a form that not only provides an introduction for intending specialists in measure theory but also meets the needs of students of probability. The theory of measure and integration is presented for general spaces, with Lebesgue measure and the Lebesgue integral considered as important examples whose special properties are obtained. The introduction to functional analysis which follows covers the material (such as the various notions of convergence) which is relevant to probability theory and also the basic theory of L2-spaces, important in modern physics. The second part of the book is an account of the fundamental theoretical ideas which underlie the applications of probability in statistics and elsewhere, developed from the results obtained in the first part. A large number of examples is included; these form an essential part of the development |
| Beschreibung: | Title from publisher's bibliographic system (viewed on 05 Oct 2015) |
| Beschreibung: | 1 online resource (x, 401 pages) |
| ISBN: | 9780511897214 |
| DOI: | 10.1017/CBO9780511897214 |
Internformat
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| 100 | 1 | |a Kingman, J. F. C. |e Verfasser |4 aut | |
| 245 | 1 | 0 | |a Introduction to measure and probability |c by J.F.C. Kingman and S.J. Taylor |
| 246 | 1 | 3 | |a Introduction to Measure & Probability |
| 264 | 1 | |a Cambridge |b Cambridge University Press |c 1966 | |
| 300 | |a 1 online resource (x, 401 pages) | ||
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| 500 | |a Title from publisher's bibliographic system (viewed on 05 Oct 2015) | ||
| 505 | 8 | |a Theory of sets -- Point set topology -- Set functions -- Construction and properties of measures -- Definitions and properties of the integral -- Related spaces and measures -- The space of measurable functions -- Linear functionals -- Structure of measures in special spaces -- What is probability? -- Random variables -- Characteristic functions -- Independence -- Finite collections of random variables -- Stochastic processes | |
| 520 | |a The authors believe that a proper treatment of probability theory requires an adequate background in the theory of finite measures in general spaces. The first part of their book sets out this material in a form that not only provides an introduction for intending specialists in measure theory but also meets the needs of students of probability. The theory of measure and integration is presented for general spaces, with Lebesgue measure and the Lebesgue integral considered as important examples whose special properties are obtained. The introduction to functional analysis which follows covers the material (such as the various notions of convergence) which is relevant to probability theory and also the basic theory of L2-spaces, important in modern physics. The second part of the book is an account of the fundamental theoretical ideas which underlie the applications of probability in statistics and elsewhere, developed from the results obtained in the first part. A large number of examples is included; these form an essential part of the development | ||
| 650 | 4 | |a Probabilities | |
| 650 | 4 | |a Measure theory | |
| 650 | 4 | |a Integrals, Generalized | |
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Datensatz im Suchindex
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| any_adam_object | |
| author | Kingman, J. F. C. |
| author_facet | Kingman, J. F. C. |
| author_role | aut |
| author_sort | Kingman, J. F. C. |
| author_variant | j f c k jfc jfck |
| building | Verbundindex |
| bvnumber | BV043945793 |
| classification_rvk | QH 170 SK 800 |
| collection | ZDB-20-CBO |
| contents | Theory of sets -- Point set topology -- Set functions -- Construction and properties of measures -- Definitions and properties of the integral -- Related spaces and measures -- The space of measurable functions -- Linear functionals -- Structure of measures in special spaces -- What is probability? -- Random variables -- Characteristic functions -- Independence -- Finite collections of random variables -- Stochastic processes |
| ctrlnum | (ZDB-20-CBO)CR9780511897214 (OCoLC)859644472 (DE-599)BVBBV043945793 |
| dewey-full | 517.52 |
| dewey-hundreds | 500 - Natural sciences and mathematics |
| dewey-ones | 517 - [Unassigned] |
| dewey-raw | 517.52 |
| dewey-search | 517.52 |
| dewey-sort | 3517.52 |
| dewey-tens | 510 - Mathematics |
| discipline | Mathematik Wirtschaftswissenschaften |
| doi_str_mv | 10.1017/CBO9780511897214 |
| format | Electronic eBook |
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| id | DE-604.BV043945793 |
| illustrated | Not Illustrated |
| indexdate | 2024-07-10T07:39:24Z |
| institution | BVB |
| isbn | 9780511897214 |
| language | English |
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| oclc_num | 859644472 |
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| owner_facet | DE-12 DE-92 |
| physical | 1 online resource (x, 401 pages) |
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| publishDate | 1966 |
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| publisher | Cambridge University Press |
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| spelling | Kingman, J. F. C. Verfasser aut Introduction to measure and probability by J.F.C. Kingman and S.J. Taylor Introduction to Measure & Probability Cambridge Cambridge University Press 1966 1 online resource (x, 401 pages) txt rdacontent c rdamedia cr rdacarrier Title from publisher's bibliographic system (viewed on 05 Oct 2015) Theory of sets -- Point set topology -- Set functions -- Construction and properties of measures -- Definitions and properties of the integral -- Related spaces and measures -- The space of measurable functions -- Linear functionals -- Structure of measures in special spaces -- What is probability? -- Random variables -- Characteristic functions -- Independence -- Finite collections of random variables -- Stochastic processes The authors believe that a proper treatment of probability theory requires an adequate background in the theory of finite measures in general spaces. The first part of their book sets out this material in a form that not only provides an introduction for intending specialists in measure theory but also meets the needs of students of probability. The theory of measure and integration is presented for general spaces, with Lebesgue measure and the Lebesgue integral considered as important examples whose special properties are obtained. The introduction to functional analysis which follows covers the material (such as the various notions of convergence) which is relevant to probability theory and also the basic theory of L2-spaces, important in modern physics. The second part of the book is an account of the fundamental theoretical ideas which underlie the applications of probability in statistics and elsewhere, developed from the results obtained in the first part. A large number of examples is included; these form an essential part of the development Probabilities Measure theory Integrals, Generalized Wahrscheinlichkeitsrechnung (DE-588)4064324-4 gnd rswk-swf Maßtheorie (DE-588)4074626-4 gnd rswk-swf Maßtheorie (DE-588)4074626-4 s Wahrscheinlichkeitsrechnung (DE-588)4064324-4 s 1\p DE-604 Taylor, S. J. Sonstige oth Erscheint auch als Druckausgabe 978-0-521-05888-9 Erscheint auch als Druckausgabe 978-0-521-09032-2 https://doi.org/10.1017/CBO9780511897214 Verlag URL des Erstveröffentlichers Volltext 1\p cgwrk 20201028 DE-101 https://d-nb.info/provenance/plan#cgwrk |
| spellingShingle | Kingman, J. F. C. Introduction to measure and probability Theory of sets -- Point set topology -- Set functions -- Construction and properties of measures -- Definitions and properties of the integral -- Related spaces and measures -- The space of measurable functions -- Linear functionals -- Structure of measures in special spaces -- What is probability? -- Random variables -- Characteristic functions -- Independence -- Finite collections of random variables -- Stochastic processes Probabilities Measure theory Integrals, Generalized Wahrscheinlichkeitsrechnung (DE-588)4064324-4 gnd Maßtheorie (DE-588)4074626-4 gnd |
| subject_GND | (DE-588)4064324-4 (DE-588)4074626-4 |
| title | Introduction to measure and probability |
| title_alt | Introduction to Measure & Probability |
| title_auth | Introduction to measure and probability |
| title_exact_search | Introduction to measure and probability |
| title_full | Introduction to measure and probability by J.F.C. Kingman and S.J. Taylor |
| title_fullStr | Introduction to measure and probability by J.F.C. Kingman and S.J. Taylor |
| title_full_unstemmed | Introduction to measure and probability by J.F.C. Kingman and S.J. Taylor |
| title_short | Introduction to measure and probability |
| title_sort | introduction to measure and probability |
| topic | Probabilities Measure theory Integrals, Generalized Wahrscheinlichkeitsrechnung (DE-588)4064324-4 gnd Maßtheorie (DE-588)4074626-4 gnd |
| topic_facet | Probabilities Measure theory Integrals, Generalized Wahrscheinlichkeitsrechnung Maßtheorie |
| url | https://doi.org/10.1017/CBO9780511897214 |
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