Exact Confidence Bounds when Sampling from Small Finite Universes: An Easy Reference Based on the Hypergeometric Distribution
Gespeichert in:
1. Verfasser: | |
---|---|
Format: | Elektronisch E-Book |
Sprache: | English |
Veröffentlicht: |
New York, NY
Springer New York
1991
|
Schriftenreihe: | Lecture Notes in Statistics
66 |
Schlagworte: | |
Online-Zugang: | Volltext |
Beschreibung: | There is a very simple and fundamental concept· to much of probability and statistics that can be conveyed using the following problem. PROBLEM. Assume a finite set (universe) of N units where A of the units have a particular attribute. The value of N is known while the value of A is unknown. If a proper subset (sample) of size n is selected randomly and a of the units in the subset are observed to have the particular attribute, what can be said about the unknown value of A? The problem is not new and almost anyone can describe several situations where a particular problem could be presented in this setting. Some recent references with different focuses include Cochran (1977); Williams (1978); Hajek (1981); Stuart (1984); Cassel, Samdal, and Wretman (1977); and Johnson and Kotz (1977). We focus on confidence interval estimation of A. Several methods for exact confidence interval estimation of A exist (Buonaccorsi, 1987, and Peskun, 1990), and this volume presents the theory and an extensive Table for one of them. One of the important contributions in Neyman (1934) is a discussion of the meaning of confidence interval estimation and its relationship with hypothesis testing which we will call the Neyman Approach. In Chapter 3 and following Neyman's Approach for simple random sampling (without replacement), we present an elementary development of exact confidence interval estimation of A as a response to the specific problem cited above |
Beschreibung: | 1 Online-Ressource (XVI, 431p. 10 illus) |
ISBN: | 9781461231400 9780387975153 |
ISSN: | 0930-0325 |
DOI: | 10.1007/978-1-4612-3140-0 |
Internformat
MARC
LEADER | 00000nmm a2200000zcb4500 | ||
---|---|---|---|
001 | BV042420107 | ||
003 | DE-604 | ||
005 | 00000000000000.0 | ||
007 | cr|uuu---uuuuu | ||
008 | 150317s1991 |||| o||u| ||||||eng d | ||
020 | |a 9781461231400 |c Online |9 978-1-4612-3140-0 | ||
020 | |a 9780387975153 |c Print |9 978-0-387-97515-3 | ||
024 | 7 | |a 10.1007/978-1-4612-3140-0 |2 doi | |
035 | |a (OCoLC)863759284 | ||
035 | |a (DE-599)BVBBV042420107 | ||
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 519.5 |2 23 | |
084 | |a MAT 000 |2 stub | ||
100 | 1 | |a Wright, Tommy |e Verfasser |4 aut | |
245 | 1 | 0 | |a Exact Confidence Bounds when Sampling from Small Finite Universes |b An Easy Reference Based on the Hypergeometric Distribution |c by Tommy Wright |
264 | 1 | |a New York, NY |b Springer New York |c 1991 | |
300 | |a 1 Online-Ressource (XVI, 431p. 10 illus) | ||
336 | |b txt |2 rdacontent | ||
337 | |b c |2 rdamedia | ||
338 | |b cr |2 rdacarrier | ||
490 | 0 | |a Lecture Notes in Statistics |v 66 |x 0930-0325 | |
500 | |a There is a very simple and fundamental concept· to much of probability and statistics that can be conveyed using the following problem. PROBLEM. Assume a finite set (universe) of N units where A of the units have a particular attribute. The value of N is known while the value of A is unknown. If a proper subset (sample) of size n is selected randomly and a of the units in the subset are observed to have the particular attribute, what can be said about the unknown value of A? The problem is not new and almost anyone can describe several situations where a particular problem could be presented in this setting. Some recent references with different focuses include Cochran (1977); Williams (1978); Hajek (1981); Stuart (1984); Cassel, Samdal, and Wretman (1977); and Johnson and Kotz (1977). We focus on confidence interval estimation of A. Several methods for exact confidence interval estimation of A exist (Buonaccorsi, 1987, and Peskun, 1990), and this volume presents the theory and an extensive Table for one of them. One of the important contributions in Neyman (1934) is a discussion of the meaning of confidence interval estimation and its relationship with hypothesis testing which we will call the Neyman Approach. In Chapter 3 and following Neyman's Approach for simple random sampling (without replacement), we present an elementary development of exact confidence interval estimation of A as a response to the specific problem cited above | ||
650 | 4 | |a Statistics | |
650 | 4 | |a Statistics, general | |
650 | 4 | |a Statistik | |
650 | 0 | 7 | |a Hypergeometrische Verteilung |0 (DE-588)4161062-3 |2 gnd |9 rswk-swf |
650 | 0 | 7 | |a Tabelle |0 (DE-588)4184303-4 |2 gnd |9 rswk-swf |
650 | 0 | 7 | |a Bereichsschätzung |0 (DE-588)4140553-5 |2 gnd |9 rswk-swf |
650 | 0 | 7 | |a Stichprobe |0 (DE-588)4057502-0 |2 gnd |9 rswk-swf |
689 | 0 | 0 | |a Stichprobe |0 (DE-588)4057502-0 |D s |
689 | 0 | 1 | |a Hypergeometrische Verteilung |0 (DE-588)4161062-3 |D s |
689 | 0 | 2 | |a Bereichsschätzung |0 (DE-588)4140553-5 |D s |
689 | 0 | 3 | |a Tabelle |0 (DE-588)4184303-4 |D s |
689 | 0 | |8 1\p |5 DE-604 | |
856 | 4 | 0 | |u https://doi.org/10.1007/978-1-4612-3140-0 |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:BVB01-027855524 | ||
883 | 1 | |8 1\p |a cgwrk |d 20201028 |q DE-101 |u https://d-nb.info/provenance/plan#cgwrk |
Datensatz im Suchindex
_version_ | 1804153091583377408 |
---|---|
any_adam_object | |
author | Wright, Tommy |
author_facet | Wright, Tommy |
author_role | aut |
author_sort | Wright, Tommy |
author_variant | t w tw |
building | Verbundindex |
bvnumber | BV042420107 |
classification_tum | MAT 000 |
collection | ZDB-2-SMA ZDB-2-BAE |
ctrlnum | (OCoLC)863759284 (DE-599)BVBBV042420107 |
dewey-full | 519.5 |
dewey-hundreds | 500 - Natural sciences and mathematics |
dewey-ones | 519 - Probabilities and applied mathematics |
dewey-raw | 519.5 |
dewey-search | 519.5 |
dewey-sort | 3519.5 |
dewey-tens | 510 - Mathematics |
discipline | Mathematik |
doi_str_mv | 10.1007/978-1-4612-3140-0 |
format | Electronic eBook |
fullrecord | <?xml version="1.0" encoding="UTF-8"?><collection xmlns="http://www.loc.gov/MARC21/slim"><record><leader>03396nmm a2200517zcb4500</leader><controlfield tag="001">BV042420107</controlfield><controlfield tag="003">DE-604</controlfield><controlfield tag="005">00000000000000.0</controlfield><controlfield tag="007">cr|uuu---uuuuu</controlfield><controlfield tag="008">150317s1991 |||| o||u| ||||||eng d</controlfield><datafield tag="020" ind1=" " ind2=" "><subfield code="a">9781461231400</subfield><subfield code="c">Online</subfield><subfield code="9">978-1-4612-3140-0</subfield></datafield><datafield tag="020" ind1=" " ind2=" "><subfield code="a">9780387975153</subfield><subfield code="c">Print</subfield><subfield code="9">978-0-387-97515-3</subfield></datafield><datafield tag="024" ind1="7" ind2=" "><subfield code="a">10.1007/978-1-4612-3140-0</subfield><subfield code="2">doi</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(OCoLC)863759284</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(DE-599)BVBBV042420107</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">519.5</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">Wright, Tommy</subfield><subfield code="e">Verfasser</subfield><subfield code="4">aut</subfield></datafield><datafield tag="245" ind1="1" ind2="0"><subfield code="a">Exact Confidence Bounds when Sampling from Small Finite Universes</subfield><subfield code="b">An Easy Reference Based on the Hypergeometric Distribution</subfield><subfield code="c">by Tommy Wright</subfield></datafield><datafield tag="264" ind1=" " ind2="1"><subfield code="a">New York, NY</subfield><subfield code="b">Springer New York</subfield><subfield code="c">1991</subfield></datafield><datafield tag="300" ind1=" " ind2=" "><subfield code="a">1 Online-Ressource (XVI, 431p. 10 illus)</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">Lecture Notes in Statistics</subfield><subfield code="v">66</subfield><subfield code="x">0930-0325</subfield></datafield><datafield tag="500" ind1=" " ind2=" "><subfield code="a">There is a very simple and fundamental concept· to much of probability and statistics that can be conveyed using the following problem. PROBLEM. Assume a finite set (universe) of N units where A of the units have a particular attribute. The value of N is known while the value of A is unknown. If a proper subset (sample) of size n is selected randomly and a of the units in the subset are observed to have the particular attribute, what can be said about the unknown value of A? The problem is not new and almost anyone can describe several situations where a particular problem could be presented in this setting. Some recent references with different focuses include Cochran (1977); Williams (1978); Hajek (1981); Stuart (1984); Cassel, Samdal, and Wretman (1977); and Johnson and Kotz (1977). We focus on confidence interval estimation of A. Several methods for exact confidence interval estimation of A exist (Buonaccorsi, 1987, and Peskun, 1990), and this volume presents the theory and an extensive Table for one of them. One of the important contributions in Neyman (1934) is a discussion of the meaning of confidence interval estimation and its relationship with hypothesis testing which we will call the Neyman Approach. In Chapter 3 and following Neyman's Approach for simple random sampling (without replacement), we present an elementary development of exact confidence interval estimation of A as a response to the specific problem cited above</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Statistics</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Statistics, general</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Statistik</subfield></datafield><datafield tag="650" ind1="0" ind2="7"><subfield code="a">Hypergeometrische Verteilung</subfield><subfield code="0">(DE-588)4161062-3</subfield><subfield code="2">gnd</subfield><subfield code="9">rswk-swf</subfield></datafield><datafield tag="650" ind1="0" ind2="7"><subfield code="a">Tabelle</subfield><subfield code="0">(DE-588)4184303-4</subfield><subfield code="2">gnd</subfield><subfield code="9">rswk-swf</subfield></datafield><datafield tag="650" ind1="0" ind2="7"><subfield code="a">Bereichsschätzung</subfield><subfield code="0">(DE-588)4140553-5</subfield><subfield code="2">gnd</subfield><subfield code="9">rswk-swf</subfield></datafield><datafield tag="650" ind1="0" ind2="7"><subfield code="a">Stichprobe</subfield><subfield code="0">(DE-588)4057502-0</subfield><subfield code="2">gnd</subfield><subfield code="9">rswk-swf</subfield></datafield><datafield tag="689" ind1="0" ind2="0"><subfield code="a">Stichprobe</subfield><subfield code="0">(DE-588)4057502-0</subfield><subfield code="D">s</subfield></datafield><datafield tag="689" ind1="0" ind2="1"><subfield code="a">Hypergeometrische Verteilung</subfield><subfield code="0">(DE-588)4161062-3</subfield><subfield code="D">s</subfield></datafield><datafield tag="689" ind1="0" ind2="2"><subfield code="a">Bereichsschätzung</subfield><subfield code="0">(DE-588)4140553-5</subfield><subfield code="D">s</subfield></datafield><datafield tag="689" ind1="0" ind2="3"><subfield code="a">Tabelle</subfield><subfield code="0">(DE-588)4184303-4</subfield><subfield code="D">s</subfield></datafield><datafield tag="689" ind1="0" ind2=" "><subfield code="8">1\p</subfield><subfield code="5">DE-604</subfield></datafield><datafield tag="856" ind1="4" ind2="0"><subfield code="u">https://doi.org/10.1007/978-1-4612-3140-0</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:BVB01-027855524</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></record></collection> |
id | DE-604.BV042420107 |
illustrated | Not Illustrated |
indexdate | 2024-07-10T01:21:06Z |
institution | BVB |
isbn | 9781461231400 9780387975153 |
issn | 0930-0325 |
language | English |
oai_aleph_id | oai:aleph.bib-bvb.de:BVB01-027855524 |
oclc_num | 863759284 |
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 (XVI, 431p. 10 illus) |
psigel | ZDB-2-SMA ZDB-2-BAE ZDB-2-SMA_Archive |
publishDate | 1991 |
publishDateSearch | 1991 |
publishDateSort | 1991 |
publisher | Springer New York |
record_format | marc |
series2 | Lecture Notes in Statistics |
spelling | Wright, Tommy Verfasser aut Exact Confidence Bounds when Sampling from Small Finite Universes An Easy Reference Based on the Hypergeometric Distribution by Tommy Wright New York, NY Springer New York 1991 1 Online-Ressource (XVI, 431p. 10 illus) txt rdacontent c rdamedia cr rdacarrier Lecture Notes in Statistics 66 0930-0325 There is a very simple and fundamental concept· to much of probability and statistics that can be conveyed using the following problem. PROBLEM. Assume a finite set (universe) of N units where A of the units have a particular attribute. The value of N is known while the value of A is unknown. If a proper subset (sample) of size n is selected randomly and a of the units in the subset are observed to have the particular attribute, what can be said about the unknown value of A? The problem is not new and almost anyone can describe several situations where a particular problem could be presented in this setting. Some recent references with different focuses include Cochran (1977); Williams (1978); Hajek (1981); Stuart (1984); Cassel, Samdal, and Wretman (1977); and Johnson and Kotz (1977). We focus on confidence interval estimation of A. Several methods for exact confidence interval estimation of A exist (Buonaccorsi, 1987, and Peskun, 1990), and this volume presents the theory and an extensive Table for one of them. One of the important contributions in Neyman (1934) is a discussion of the meaning of confidence interval estimation and its relationship with hypothesis testing which we will call the Neyman Approach. In Chapter 3 and following Neyman's Approach for simple random sampling (without replacement), we present an elementary development of exact confidence interval estimation of A as a response to the specific problem cited above Statistics Statistics, general Statistik Hypergeometrische Verteilung (DE-588)4161062-3 gnd rswk-swf Tabelle (DE-588)4184303-4 gnd rswk-swf Bereichsschätzung (DE-588)4140553-5 gnd rswk-swf Stichprobe (DE-588)4057502-0 gnd rswk-swf Stichprobe (DE-588)4057502-0 s Hypergeometrische Verteilung (DE-588)4161062-3 s Bereichsschätzung (DE-588)4140553-5 s Tabelle (DE-588)4184303-4 s 1\p DE-604 https://doi.org/10.1007/978-1-4612-3140-0 Verlag Volltext 1\p cgwrk 20201028 DE-101 https://d-nb.info/provenance/plan#cgwrk |
spellingShingle | Wright, Tommy Exact Confidence Bounds when Sampling from Small Finite Universes An Easy Reference Based on the Hypergeometric Distribution Statistics Statistics, general Statistik Hypergeometrische Verteilung (DE-588)4161062-3 gnd Tabelle (DE-588)4184303-4 gnd Bereichsschätzung (DE-588)4140553-5 gnd Stichprobe (DE-588)4057502-0 gnd |
subject_GND | (DE-588)4161062-3 (DE-588)4184303-4 (DE-588)4140553-5 (DE-588)4057502-0 |
title | Exact Confidence Bounds when Sampling from Small Finite Universes An Easy Reference Based on the Hypergeometric Distribution |
title_auth | Exact Confidence Bounds when Sampling from Small Finite Universes An Easy Reference Based on the Hypergeometric Distribution |
title_exact_search | Exact Confidence Bounds when Sampling from Small Finite Universes An Easy Reference Based on the Hypergeometric Distribution |
title_full | Exact Confidence Bounds when Sampling from Small Finite Universes An Easy Reference Based on the Hypergeometric Distribution by Tommy Wright |
title_fullStr | Exact Confidence Bounds when Sampling from Small Finite Universes An Easy Reference Based on the Hypergeometric Distribution by Tommy Wright |
title_full_unstemmed | Exact Confidence Bounds when Sampling from Small Finite Universes An Easy Reference Based on the Hypergeometric Distribution by Tommy Wright |
title_short | Exact Confidence Bounds when Sampling from Small Finite Universes |
title_sort | exact confidence bounds when sampling from small finite universes an easy reference based on the hypergeometric distribution |
title_sub | An Easy Reference Based on the Hypergeometric Distribution |
topic | Statistics Statistics, general Statistik Hypergeometrische Verteilung (DE-588)4161062-3 gnd Tabelle (DE-588)4184303-4 gnd Bereichsschätzung (DE-588)4140553-5 gnd Stichprobe (DE-588)4057502-0 gnd |
topic_facet | Statistics Statistics, general Statistik Hypergeometrische Verteilung Tabelle Bereichsschätzung Stichprobe |
url | https://doi.org/10.1007/978-1-4612-3140-0 |
work_keys_str_mv | AT wrighttommy exactconfidenceboundswhensamplingfromsmallfiniteuniversesaneasyreferencebasedonthehypergeometricdistribution |