Multiple correspondence analysis for the social sciences:
Multiple correspondence analysis (MCA) is a statistical technique that first and foremost has become known through the work of the late Pierre Bourdieu (1930?2002) This book will introduce readers to the fundamental properties, procedures and rules of interpretation of the most commonly used forms o...
Gespeichert in:
| 1. Verfasser: | |
|---|---|
| Format: | Elektronisch E-Book |
| Sprache: | English |
| Veröffentlicht: |
Abingdon, Oxon
Routledge
2018
|
| Schlagworte: | |
| Online-Zugang: | URL des Erstveroeffentlichers |
| Zusammenfassung: | Multiple correspondence analysis (MCA) is a statistical technique that first and foremost has become known through the work of the late Pierre Bourdieu (1930?2002) This book will introduce readers to the fundamental properties, procedures and rules of interpretation of the most commonly used forms of correspondence analysis. The book is written as a non-technical introduction, intended for the advanced undergraduate level and onwards. MCA represents and models data sets as clouds of points in a multidimensional Euclidean space. The interpretation of the data is based on these clouds of points. In seven chapters, this non-technical book will provide the reader with a comprehensive introduction and the needed knowledge to do analyses on his/her own: CA, MCA, specific MCA, the integration of MCA and variance analysis, of MCA and ascending hierarchical cluster analysis and class-specific MCA on subgroups. Special attention will be given to the construction of social spaces, to the construction of typologies and to group internal oppositions. This is a book on data analysis for the social sciences rather than a book on statistics. The main emphasis is on how to apply MCA to the analysis of practical research questions. It does not require a solid understanding of statistics and/or mathematics, and provides the reader with the needed knowledge to do analyses on his/her own |
| Beschreibung: | 1 online resource |
| ISBN: | 9781315516233 1315516233 9781315516257 9781315516240 1315516241 9781315516226 1315516225 131551625X |
Internformat
MARC
| LEADER | 00000nmm a2200000zc 4500 | ||
|---|---|---|---|
| 001 | BV047013061 | ||
| 003 | DE-604 | ||
| 005 | 00000000000000.0 | ||
| 007 | cr|uuu---uuuuu | ||
| 008 | 201118s2018 |||| o||u| ||||||eng d | ||
| 020 | |a 9781315516233 |9 978-1-315-51623-3 | ||
| 020 | |a 1315516233 |9 1-315-51623-3 | ||
| 020 | |a 9781315516257 |9 978-1-315-51625-7 | ||
| 020 | |a 9781315516240 |9 978-1-315-51624-0 | ||
| 020 | |a 1315516241 |9 1-315-51624-1 | ||
| 020 | |a 9781315516226 |9 978-1-315-51622-6 | ||
| 020 | |a 1315516225 |9 1-315-51622-5 | ||
| 020 | |a 131551625X |9 1-315-51625-X | ||
| 020 | |a 9781315516257 |9 978-1-315-51625-7 | ||
| 035 | |a (ZDB-7-TFC)9781315516233 | ||
| 035 | |a (DE-599)BVBBV047013061 | ||
| 040 | |a DE-604 |b ger |e rda | ||
| 041 | 0 | |a eng | |
| 082 | 0 | |a 519.5/37 |2 23 | |
| 100 | 1 | |a Hjellbrekke, Johs. |e Verfasser |4 aut | |
| 245 | 1 | 0 | |a Multiple correspondence analysis for the social sciences |c Johs. Hjellbrekke |
| 264 | 1 | |a Abingdon, Oxon |b Routledge |c 2018 | |
| 300 | |a 1 online resource | ||
| 336 | |b txt |2 rdacontent | ||
| 337 | |b c |2 rdamedia | ||
| 338 | |b cr |2 rdacarrier | ||
| 520 | |a Multiple correspondence analysis (MCA) is a statistical technique that first and foremost has become known through the work of the late Pierre Bourdieu (1930?2002) This book will introduce readers to the fundamental properties, procedures and rules of interpretation of the most commonly used forms of correspondence analysis. The book is written as a non-technical introduction, intended for the advanced undergraduate level and onwards. MCA represents and models data sets as clouds of points in a multidimensional Euclidean space. The interpretation of the data is based on these clouds of points. In seven chapters, this non-technical book will provide the reader with a comprehensive introduction and the needed knowledge to do analyses on his/her own: CA, MCA, specific MCA, the integration of MCA and variance analysis, of MCA and ascending hierarchical cluster analysis and class-specific MCA on subgroups. Special attention will be given to the construction of social spaces, to the construction of typologies and to group internal oppositions. This is a book on data analysis for the social sciences rather than a book on statistics. The main emphasis is on how to apply MCA to the analysis of practical research questions. It does not require a solid understanding of statistics and/or mathematics, and provides the reader with the needed knowledge to do analyses on his/her own | ||
| 650 | 4 | |a Social sciences / Statistical methods | |
| 650 | 4 | |a Correspondence analysis (Statistics) | |
| 856 | 4 | 0 | |u https://www.taylorfrancis.com/books/9781315516257 |x Verlag |z URL des Erstveroeffentlichers |3 Volltext |
| 912 | |a ZDB-7-TFC | ||
| 999 | |a oai:aleph.bib-bvb.de:BVB01-032420597 | ||
Datensatz im Suchindex
| _version_ | 1804181971366051840 |
|---|---|
| adam_txt | |
| any_adam_object | |
| any_adam_object_boolean | |
| author | Hjellbrekke, Johs |
| author_facet | Hjellbrekke, Johs |
| author_role | aut |
| author_sort | Hjellbrekke, Johs |
| author_variant | j h jh |
| building | Verbundindex |
| bvnumber | BV047013061 |
| collection | ZDB-7-TFC |
| ctrlnum | (ZDB-7-TFC)9781315516233 (DE-599)BVBBV047013061 |
| dewey-full | 519.5/37 |
| dewey-hundreds | 500 - Natural sciences and mathematics |
| dewey-ones | 519 - Probabilities and applied mathematics |
| dewey-raw | 519.5/37 |
| dewey-search | 519.5/37 |
| dewey-sort | 3519.5 237 |
| dewey-tens | 510 - Mathematics |
| discipline | Mathematik |
| discipline_str_mv | Mathematik |
| format | Electronic eBook |
| fullrecord | <?xml version="1.0" encoding="UTF-8"?><collection xmlns="http://www.loc.gov/MARC21/slim"><record><leader>02776nmm a2200409zc 4500</leader><controlfield tag="001">BV047013061</controlfield><controlfield tag="003">DE-604</controlfield><controlfield tag="005">00000000000000.0</controlfield><controlfield tag="007">cr|uuu---uuuuu</controlfield><controlfield tag="008">201118s2018 |||| o||u| ||||||eng d</controlfield><datafield tag="020" ind1=" " ind2=" "><subfield code="a">9781315516233</subfield><subfield code="9">978-1-315-51623-3</subfield></datafield><datafield tag="020" ind1=" " ind2=" "><subfield code="a">1315516233</subfield><subfield code="9">1-315-51623-3</subfield></datafield><datafield tag="020" ind1=" " ind2=" "><subfield code="a">9781315516257</subfield><subfield code="9">978-1-315-51625-7</subfield></datafield><datafield tag="020" ind1=" " ind2=" "><subfield code="a">9781315516240</subfield><subfield code="9">978-1-315-51624-0</subfield></datafield><datafield tag="020" ind1=" " ind2=" "><subfield code="a">1315516241</subfield><subfield code="9">1-315-51624-1</subfield></datafield><datafield tag="020" ind1=" " ind2=" "><subfield code="a">9781315516226</subfield><subfield code="9">978-1-315-51622-6</subfield></datafield><datafield tag="020" ind1=" " ind2=" "><subfield code="a">1315516225</subfield><subfield code="9">1-315-51622-5</subfield></datafield><datafield tag="020" ind1=" " ind2=" "><subfield code="a">131551625X</subfield><subfield code="9">1-315-51625-X</subfield></datafield><datafield tag="020" ind1=" " ind2=" "><subfield code="a">9781315516257</subfield><subfield code="9">978-1-315-51625-7</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(ZDB-7-TFC)9781315516233</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(DE-599)BVBBV047013061</subfield></datafield><datafield tag="040" ind1=" " ind2=" "><subfield code="a">DE-604</subfield><subfield code="b">ger</subfield><subfield code="e">rda</subfield></datafield><datafield tag="041" ind1="0" ind2=" "><subfield code="a">eng</subfield></datafield><datafield tag="082" ind1="0" ind2=" "><subfield code="a">519.5/37</subfield><subfield code="2">23</subfield></datafield><datafield tag="100" ind1="1" ind2=" "><subfield code="a">Hjellbrekke, Johs.</subfield><subfield code="e">Verfasser</subfield><subfield code="4">aut</subfield></datafield><datafield tag="245" ind1="1" ind2="0"><subfield code="a">Multiple correspondence analysis for the social sciences</subfield><subfield code="c">Johs. Hjellbrekke</subfield></datafield><datafield tag="264" ind1=" " ind2="1"><subfield code="a">Abingdon, Oxon</subfield><subfield code="b">Routledge</subfield><subfield code="c">2018</subfield></datafield><datafield tag="300" ind1=" " ind2=" "><subfield code="a">1 online resource</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="520" ind1=" " ind2=" "><subfield code="a">Multiple correspondence analysis (MCA) is a statistical technique that first and foremost has become known through the work of the late Pierre Bourdieu (1930?2002) This book will introduce readers to the fundamental properties, procedures and rules of interpretation of the most commonly used forms of correspondence analysis. The book is written as a non-technical introduction, intended for the advanced undergraduate level and onwards. MCA represents and models data sets as clouds of points in a multidimensional Euclidean space. The interpretation of the data is based on these clouds of points. In seven chapters, this non-technical book will provide the reader with a comprehensive introduction and the needed knowledge to do analyses on his/her own: CA, MCA, specific MCA, the integration of MCA and variance analysis, of MCA and ascending hierarchical cluster analysis and class-specific MCA on subgroups. Special attention will be given to the construction of social spaces, to the construction of typologies and to group internal oppositions. This is a book on data analysis for the social sciences rather than a book on statistics. The main emphasis is on how to apply MCA to the analysis of practical research questions. It does not require a solid understanding of statistics and/or mathematics, and provides the reader with the needed knowledge to do analyses on his/her own</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Social sciences / Statistical methods</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Correspondence analysis (Statistics)</subfield></datafield><datafield tag="856" ind1="4" ind2="0"><subfield code="u">https://www.taylorfrancis.com/books/9781315516257</subfield><subfield code="x">Verlag</subfield><subfield code="z">URL des Erstveroeffentlichers</subfield><subfield code="3">Volltext</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">ZDB-7-TFC</subfield></datafield><datafield tag="999" ind1=" " ind2=" "><subfield code="a">oai:aleph.bib-bvb.de:BVB01-032420597</subfield></datafield></record></collection> |
| id | DE-604.BV047013061 |
| illustrated | Not Illustrated |
| index_date | 2024-07-03T15:58:13Z |
| indexdate | 2024-07-10T09:00:08Z |
| institution | BVB |
| isbn | 9781315516233 1315516233 9781315516257 9781315516240 1315516241 9781315516226 1315516225 131551625X |
| language | English |
| oai_aleph_id | oai:aleph.bib-bvb.de:BVB01-032420597 |
| open_access_boolean | |
| physical | 1 online resource |
| psigel | ZDB-7-TFC |
| publishDate | 2018 |
| publishDateSearch | 2018 |
| publishDateSort | 2018 |
| publisher | Routledge |
| record_format | marc |
| spelling | Hjellbrekke, Johs. Verfasser aut Multiple correspondence analysis for the social sciences Johs. Hjellbrekke Abingdon, Oxon Routledge 2018 1 online resource txt rdacontent c rdamedia cr rdacarrier Multiple correspondence analysis (MCA) is a statistical technique that first and foremost has become known through the work of the late Pierre Bourdieu (1930?2002) This book will introduce readers to the fundamental properties, procedures and rules of interpretation of the most commonly used forms of correspondence analysis. The book is written as a non-technical introduction, intended for the advanced undergraduate level and onwards. MCA represents and models data sets as clouds of points in a multidimensional Euclidean space. The interpretation of the data is based on these clouds of points. In seven chapters, this non-technical book will provide the reader with a comprehensive introduction and the needed knowledge to do analyses on his/her own: CA, MCA, specific MCA, the integration of MCA and variance analysis, of MCA and ascending hierarchical cluster analysis and class-specific MCA on subgroups. Special attention will be given to the construction of social spaces, to the construction of typologies and to group internal oppositions. This is a book on data analysis for the social sciences rather than a book on statistics. The main emphasis is on how to apply MCA to the analysis of practical research questions. It does not require a solid understanding of statistics and/or mathematics, and provides the reader with the needed knowledge to do analyses on his/her own Social sciences / Statistical methods Correspondence analysis (Statistics) https://www.taylorfrancis.com/books/9781315516257 Verlag URL des Erstveroeffentlichers Volltext |
| spellingShingle | Hjellbrekke, Johs Multiple correspondence analysis for the social sciences Social sciences / Statistical methods Correspondence analysis (Statistics) |
| title | Multiple correspondence analysis for the social sciences |
| title_auth | Multiple correspondence analysis for the social sciences |
| title_exact_search | Multiple correspondence analysis for the social sciences |
| title_exact_search_txtP | Multiple correspondence analysis for the social sciences |
| title_full | Multiple correspondence analysis for the social sciences Johs. Hjellbrekke |
| title_fullStr | Multiple correspondence analysis for the social sciences Johs. Hjellbrekke |
| title_full_unstemmed | Multiple correspondence analysis for the social sciences Johs. Hjellbrekke |
| title_short | Multiple correspondence analysis for the social sciences |
| title_sort | multiple correspondence analysis for the social sciences |
| topic | Social sciences / Statistical methods Correspondence analysis (Statistics) |
| topic_facet | Social sciences / Statistical methods Correspondence analysis (Statistics) |
| url | https://www.taylorfrancis.com/books/9781315516257 |
| work_keys_str_mv | AT hjellbrekkejohs multiplecorrespondenceanalysisforthesocialsciences |