Probability Theory: An Introductory Course
Gespeichert in:
1. Verfasser: | |
---|---|
Format: | Elektronisch E-Book |
Sprache: | English |
Veröffentlicht: |
Berlin, Heidelberg
Springer Berlin Heidelberg
1992
|
Schriftenreihe: | Springer Textbook
|
Schlagworte: | |
Online-Zugang: | Volltext |
Beschreibung: | Sinai's book leads the student through the standard material for ProbabilityTheory, with stops along the way for interesting topics such as statistical mechanics, not usually included in a book for beginners. The first part of the book covers discrete random variables, using the same approach, basedon Kolmogorov's axioms for probability, used later for the general case. The text is divided into sixteen lectures, each covering a major topic. The introductory notions and classical results are included, of course: random variables, the central limit theorem, the law of large numbers, conditional probability, random walks, etc. Sinai's style is accessible and clear, with interesting examples to accompany new ideas. Besides statistical mechanics, other interesting, less common topics found in the book are: percolation, the concept of stability in the central limit theorem and the study of probability of large deviations. Little more than a standard undergraduate course in analysis is assumed of the reader. Notions from measure theory and Lebesgue integration are introduced in the second half of the text. The book is suitable for second or third year students in mathematics, physics or other natural sciences. It could also be usedby more advanced readers who want to learn the mathematics of probability theory and some of its applications in statistical physics |
Beschreibung: | 1 Online-Ressource (VIII, 140 p) |
ISBN: | 9783662028452 9783540533481 |
ISSN: | 1431-8512 |
DOI: | 10.1007/978-3-662-02845-2 |
Internformat
MARC
LEADER | 00000nmm a2200000zc 4500 | ||
---|---|---|---|
001 | BV042423219 | ||
003 | DE-604 | ||
005 | 00000000000000.0 | ||
007 | cr|uuu---uuuuu | ||
008 | 150317s1992 |||| o||u| ||||||eng d | ||
020 | |a 9783662028452 |c Online |9 978-3-662-02845-2 | ||
020 | |a 9783540533481 |c Print |9 978-3-540-53348-1 | ||
024 | 7 | |a 10.1007/978-3-662-02845-2 |2 doi | |
035 | |a (OCoLC)863902770 | ||
035 | |a (DE-599)BVBBV042423219 | ||
040 | |a DE-604 |b ger |e aacr | ||
041 | 0 | |a eng | |
049 | |a DE-384 |a DE-703 |a DE-91 |a DE-634 | ||
082 | 0 | |a 519.2 |2 23 | |
084 | |a MAT 000 |2 stub | ||
100 | 1 | |a Sinai, Yakov G. |e Verfasser |4 aut | |
245 | 1 | 0 | |a Probability Theory |b An Introductory Course |c by Yakov G. Sinai |
264 | 1 | |a Berlin, Heidelberg |b Springer Berlin Heidelberg |c 1992 | |
300 | |a 1 Online-Ressource (VIII, 140 p) | ||
336 | |b txt |2 rdacontent | ||
337 | |b c |2 rdamedia | ||
338 | |b cr |2 rdacarrier | ||
490 | 0 | |a Springer Textbook |x 1431-8512 | |
500 | |a Sinai's book leads the student through the standard material for ProbabilityTheory, with stops along the way for interesting topics such as statistical mechanics, not usually included in a book for beginners. The first part of the book covers discrete random variables, using the same approach, basedon Kolmogorov's axioms for probability, used later for the general case. The text is divided into sixteen lectures, each covering a major topic. The introductory notions and classical results are included, of course: random variables, the central limit theorem, the law of large numbers, conditional probability, random walks, etc. Sinai's style is accessible and clear, with interesting examples to accompany new ideas. Besides statistical mechanics, other interesting, less common topics found in the book are: percolation, the concept of stability in the central limit theorem and the study of probability of large deviations. Little more than a standard undergraduate course in analysis is assumed of the reader. Notions from measure theory and Lebesgue integration are introduced in the second half of the text. The book is suitable for second or third year students in mathematics, physics or other natural sciences. It could also be usedby more advanced readers who want to learn the mathematics of probability theory and some of its applications in statistical physics | ||
650 | 4 | |a Mathematics | |
650 | 4 | |a Distribution (Probability theory) | |
650 | 4 | |a Probability Theory and Stochastic Processes | |
650 | 4 | |a Mathematik | |
650 | 0 | 7 | |a Wahrscheinlichkeitstheorie |0 (DE-588)4079013-7 |2 gnd |9 rswk-swf |
650 | 0 | 7 | |a Wahrscheinlichkeitsrechnung |0 (DE-588)4064324-4 |2 gnd |9 rswk-swf |
655 | 7 | |8 1\p |0 (DE-588)4151278-9 |a Einführung |2 gnd-content | |
689 | 0 | 0 | |a Wahrscheinlichkeitsrechnung |0 (DE-588)4064324-4 |D s |
689 | 0 | |8 2\p |5 DE-604 | |
689 | 1 | 0 | |a Wahrscheinlichkeitstheorie |0 (DE-588)4079013-7 |D s |
689 | 1 | |8 3\p |5 DE-604 | |
856 | 4 | 0 | |u https://doi.org/10.1007/978-3-662-02845-2 |x Verlag |3 Volltext |
912 | |a ZDB-2-SMA |a ZDB-2-BAE | ||
940 | 1 | |q ZDB-2-SMA_Archive | |
999 | |a oai:aleph.bib-bvb.de:BVB01-027858636 | ||
883 | 1 | |8 1\p |a cgwrk |d 20201028 |q DE-101 |u https://d-nb.info/provenance/plan#cgwrk | |
883 | 1 | |8 2\p |a cgwrk |d 20201028 |q DE-101 |u https://d-nb.info/provenance/plan#cgwrk | |
883 | 1 | |8 3\p |a cgwrk |d 20201028 |q DE-101 |u https://d-nb.info/provenance/plan#cgwrk |
Datensatz im Suchindex
_version_ | 1804153098703208448 |
---|---|
any_adam_object | |
author | Sinai, Yakov G. |
author_facet | Sinai, Yakov G. |
author_role | aut |
author_sort | Sinai, Yakov G. |
author_variant | y g s yg ygs |
building | Verbundindex |
bvnumber | BV042423219 |
classification_tum | MAT 000 |
collection | ZDB-2-SMA ZDB-2-BAE |
ctrlnum | (OCoLC)863902770 (DE-599)BVBBV042423219 |
dewey-full | 519.2 |
dewey-hundreds | 500 - Natural sciences and mathematics |
dewey-ones | 519 - Probabilities and applied mathematics |
dewey-raw | 519.2 |
dewey-search | 519.2 |
dewey-sort | 3519.2 |
dewey-tens | 510 - Mathematics |
discipline | Mathematik |
doi_str_mv | 10.1007/978-3-662-02845-2 |
format | Electronic eBook |
fullrecord | <?xml version="1.0" encoding="UTF-8"?><collection xmlns="http://www.loc.gov/MARC21/slim"><record><leader>03369nmm a2200529zc 4500</leader><controlfield tag="001">BV042423219</controlfield><controlfield tag="003">DE-604</controlfield><controlfield tag="005">00000000000000.0</controlfield><controlfield tag="007">cr|uuu---uuuuu</controlfield><controlfield tag="008">150317s1992 |||| o||u| ||||||eng d</controlfield><datafield tag="020" ind1=" " ind2=" "><subfield code="a">9783662028452</subfield><subfield code="c">Online</subfield><subfield code="9">978-3-662-02845-2</subfield></datafield><datafield tag="020" ind1=" " ind2=" "><subfield code="a">9783540533481</subfield><subfield code="c">Print</subfield><subfield code="9">978-3-540-53348-1</subfield></datafield><datafield tag="024" ind1="7" ind2=" "><subfield code="a">10.1007/978-3-662-02845-2</subfield><subfield code="2">doi</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(OCoLC)863902770</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(DE-599)BVBBV042423219</subfield></datafield><datafield tag="040" ind1=" " ind2=" "><subfield code="a">DE-604</subfield><subfield code="b">ger</subfield><subfield code="e">aacr</subfield></datafield><datafield tag="041" ind1="0" ind2=" "><subfield code="a">eng</subfield></datafield><datafield tag="049" ind1=" " ind2=" "><subfield code="a">DE-384</subfield><subfield code="a">DE-703</subfield><subfield code="a">DE-91</subfield><subfield code="a">DE-634</subfield></datafield><datafield tag="082" ind1="0" ind2=" "><subfield code="a">519.2</subfield><subfield code="2">23</subfield></datafield><datafield tag="084" ind1=" " ind2=" "><subfield code="a">MAT 000</subfield><subfield code="2">stub</subfield></datafield><datafield tag="100" ind1="1" ind2=" "><subfield code="a">Sinai, Yakov G.</subfield><subfield code="e">Verfasser</subfield><subfield code="4">aut</subfield></datafield><datafield tag="245" ind1="1" ind2="0"><subfield code="a">Probability Theory</subfield><subfield code="b">An Introductory Course</subfield><subfield code="c">by Yakov G. Sinai</subfield></datafield><datafield tag="264" ind1=" " ind2="1"><subfield code="a">Berlin, Heidelberg</subfield><subfield code="b">Springer Berlin Heidelberg</subfield><subfield code="c">1992</subfield></datafield><datafield tag="300" ind1=" " ind2=" "><subfield code="a">1 Online-Ressource (VIII, 140 p)</subfield></datafield><datafield tag="336" ind1=" " ind2=" "><subfield code="b">txt</subfield><subfield code="2">rdacontent</subfield></datafield><datafield tag="337" ind1=" " ind2=" "><subfield code="b">c</subfield><subfield code="2">rdamedia</subfield></datafield><datafield tag="338" ind1=" " ind2=" "><subfield code="b">cr</subfield><subfield code="2">rdacarrier</subfield></datafield><datafield tag="490" ind1="0" ind2=" "><subfield code="a">Springer Textbook</subfield><subfield code="x">1431-8512</subfield></datafield><datafield tag="500" ind1=" " ind2=" "><subfield code="a">Sinai's book leads the student through the standard material for ProbabilityTheory, with stops along the way for interesting topics such as statistical mechanics, not usually included in a book for beginners. The first part of the book covers discrete random variables, using the same approach, basedon Kolmogorov's axioms for probability, used later for the general case. The text is divided into sixteen lectures, each covering a major topic. The introductory notions and classical results are included, of course: random variables, the central limit theorem, the law of large numbers, conditional probability, random walks, etc. Sinai's style is accessible and clear, with interesting examples to accompany new ideas. Besides statistical mechanics, other interesting, less common topics found in the book are: percolation, the concept of stability in the central limit theorem and the study of probability of large deviations. Little more than a standard undergraduate course in analysis is assumed of the reader. Notions from measure theory and Lebesgue integration are introduced in the second half of the text. The book is suitable for second or third year students in mathematics, physics or other natural sciences. It could also be usedby more advanced readers who want to learn the mathematics of probability theory and some of its applications in statistical physics</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Mathematics</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Distribution (Probability theory)</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Probability Theory and Stochastic Processes</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Mathematik</subfield></datafield><datafield tag="650" ind1="0" ind2="7"><subfield code="a">Wahrscheinlichkeitstheorie</subfield><subfield code="0">(DE-588)4079013-7</subfield><subfield code="2">gnd</subfield><subfield code="9">rswk-swf</subfield></datafield><datafield tag="650" ind1="0" ind2="7"><subfield code="a">Wahrscheinlichkeitsrechnung</subfield><subfield code="0">(DE-588)4064324-4</subfield><subfield code="2">gnd</subfield><subfield code="9">rswk-swf</subfield></datafield><datafield tag="655" ind1=" " ind2="7"><subfield code="8">1\p</subfield><subfield code="0">(DE-588)4151278-9</subfield><subfield code="a">Einführung</subfield><subfield code="2">gnd-content</subfield></datafield><datafield tag="689" ind1="0" ind2="0"><subfield code="a">Wahrscheinlichkeitsrechnung</subfield><subfield code="0">(DE-588)4064324-4</subfield><subfield code="D">s</subfield></datafield><datafield tag="689" ind1="0" ind2=" "><subfield code="8">2\p</subfield><subfield code="5">DE-604</subfield></datafield><datafield tag="689" ind1="1" ind2="0"><subfield code="a">Wahrscheinlichkeitstheorie</subfield><subfield code="0">(DE-588)4079013-7</subfield><subfield code="D">s</subfield></datafield><datafield tag="689" ind1="1" ind2=" "><subfield code="8">3\p</subfield><subfield code="5">DE-604</subfield></datafield><datafield tag="856" ind1="4" ind2="0"><subfield code="u">https://doi.org/10.1007/978-3-662-02845-2</subfield><subfield code="x">Verlag</subfield><subfield code="3">Volltext</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">ZDB-2-SMA</subfield><subfield code="a">ZDB-2-BAE</subfield></datafield><datafield tag="940" ind1="1" ind2=" "><subfield code="q">ZDB-2-SMA_Archive</subfield></datafield><datafield tag="999" ind1=" " ind2=" "><subfield code="a">oai:aleph.bib-bvb.de:BVB01-027858636</subfield></datafield><datafield tag="883" ind1="1" ind2=" "><subfield code="8">1\p</subfield><subfield code="a">cgwrk</subfield><subfield code="d">20201028</subfield><subfield code="q">DE-101</subfield><subfield code="u">https://d-nb.info/provenance/plan#cgwrk</subfield></datafield><datafield tag="883" ind1="1" ind2=" "><subfield code="8">2\p</subfield><subfield code="a">cgwrk</subfield><subfield code="d">20201028</subfield><subfield code="q">DE-101</subfield><subfield code="u">https://d-nb.info/provenance/plan#cgwrk</subfield></datafield><datafield tag="883" ind1="1" ind2=" "><subfield code="8">3\p</subfield><subfield code="a">cgwrk</subfield><subfield code="d">20201028</subfield><subfield code="q">DE-101</subfield><subfield code="u">https://d-nb.info/provenance/plan#cgwrk</subfield></datafield></record></collection> |
genre | 1\p (DE-588)4151278-9 Einführung gnd-content |
genre_facet | Einführung |
id | DE-604.BV042423219 |
illustrated | Not Illustrated |
indexdate | 2024-07-10T01:21:13Z |
institution | BVB |
isbn | 9783662028452 9783540533481 |
issn | 1431-8512 |
language | English |
oai_aleph_id | oai:aleph.bib-bvb.de:BVB01-027858636 |
oclc_num | 863902770 |
open_access_boolean | |
owner | DE-384 DE-703 DE-91 DE-BY-TUM DE-634 |
owner_facet | DE-384 DE-703 DE-91 DE-BY-TUM DE-634 |
physical | 1 Online-Ressource (VIII, 140 p) |
psigel | ZDB-2-SMA ZDB-2-BAE ZDB-2-SMA_Archive |
publishDate | 1992 |
publishDateSearch | 1992 |
publishDateSort | 1992 |
publisher | Springer Berlin Heidelberg |
record_format | marc |
series2 | Springer Textbook |
spelling | Sinai, Yakov G. Verfasser aut Probability Theory An Introductory Course by Yakov G. Sinai Berlin, Heidelberg Springer Berlin Heidelberg 1992 1 Online-Ressource (VIII, 140 p) txt rdacontent c rdamedia cr rdacarrier Springer Textbook 1431-8512 Sinai's book leads the student through the standard material for ProbabilityTheory, with stops along the way for interesting topics such as statistical mechanics, not usually included in a book for beginners. The first part of the book covers discrete random variables, using the same approach, basedon Kolmogorov's axioms for probability, used later for the general case. The text is divided into sixteen lectures, each covering a major topic. The introductory notions and classical results are included, of course: random variables, the central limit theorem, the law of large numbers, conditional probability, random walks, etc. Sinai's style is accessible and clear, with interesting examples to accompany new ideas. Besides statistical mechanics, other interesting, less common topics found in the book are: percolation, the concept of stability in the central limit theorem and the study of probability of large deviations. Little more than a standard undergraduate course in analysis is assumed of the reader. Notions from measure theory and Lebesgue integration are introduced in the second half of the text. The book is suitable for second or third year students in mathematics, physics or other natural sciences. It could also be usedby more advanced readers who want to learn the mathematics of probability theory and some of its applications in statistical physics Mathematics Distribution (Probability theory) Probability Theory and Stochastic Processes Mathematik Wahrscheinlichkeitstheorie (DE-588)4079013-7 gnd rswk-swf Wahrscheinlichkeitsrechnung (DE-588)4064324-4 gnd rswk-swf 1\p (DE-588)4151278-9 Einführung gnd-content Wahrscheinlichkeitsrechnung (DE-588)4064324-4 s 2\p DE-604 Wahrscheinlichkeitstheorie (DE-588)4079013-7 s 3\p DE-604 https://doi.org/10.1007/978-3-662-02845-2 Verlag Volltext 1\p cgwrk 20201028 DE-101 https://d-nb.info/provenance/plan#cgwrk 2\p cgwrk 20201028 DE-101 https://d-nb.info/provenance/plan#cgwrk 3\p cgwrk 20201028 DE-101 https://d-nb.info/provenance/plan#cgwrk |
spellingShingle | Sinai, Yakov G. Probability Theory An Introductory Course Mathematics Distribution (Probability theory) Probability Theory and Stochastic Processes Mathematik Wahrscheinlichkeitstheorie (DE-588)4079013-7 gnd Wahrscheinlichkeitsrechnung (DE-588)4064324-4 gnd |
subject_GND | (DE-588)4079013-7 (DE-588)4064324-4 (DE-588)4151278-9 |
title | Probability Theory An Introductory Course |
title_auth | Probability Theory An Introductory Course |
title_exact_search | Probability Theory An Introductory Course |
title_full | Probability Theory An Introductory Course by Yakov G. Sinai |
title_fullStr | Probability Theory An Introductory Course by Yakov G. Sinai |
title_full_unstemmed | Probability Theory An Introductory Course by Yakov G. Sinai |
title_short | Probability Theory |
title_sort | probability theory an introductory course |
title_sub | An Introductory Course |
topic | Mathematics Distribution (Probability theory) Probability Theory and Stochastic Processes Mathematik Wahrscheinlichkeitstheorie (DE-588)4079013-7 gnd Wahrscheinlichkeitsrechnung (DE-588)4064324-4 gnd |
topic_facet | Mathematics Distribution (Probability theory) Probability Theory and Stochastic Processes Mathematik Wahrscheinlichkeitstheorie Wahrscheinlichkeitsrechnung Einführung |
url | https://doi.org/10.1007/978-3-662-02845-2 |
work_keys_str_mv | AT sinaiyakovg probabilitytheoryanintroductorycourse |