Multiple Correspondence Analysis
Nonfiction, Social & Cultural Studies, Social Science, Statistics, Reference & Language, Reference, Research
| Author: | Professor Brigitte Le Roux, Professor Henry Rouanet | ISBN: | 9781483389462 |
| Publisher: | SAGE Publications | Publication: | December 16, 2009 |
| Imprint: | SAGE Publications, Inc | Language: | English |
| Author: | Professor Brigitte Le Roux, Professor Henry Rouanet |
| ISBN: | 9781483389462 |
| Publisher: | SAGE Publications |
| Publication: | December 16, 2009 |
| Imprint: | SAGE Publications, Inc |
| Language: | English |
Requiring no prior knowledge of correspondence analysis, this text provides a nontechnical introduction to Multiple Correspondence Analysis (MCA) as a method in its own right. The authors, Brigitte LeRoux and Henry Rouanet, present thematerial in a practical manner, keeping the needs of researchers foremost in mind.
Key Features
- Readers learn how to construct geometric spaces from relevant data, formulate questions of interest, and link statistical interpretation to geometric representations.
- They also learn how to perform structured data analysis and to draw inferential conclusions from MCA.
- The text uses real examples to help explain concepts.
- The authors stress the distinctive capacity of MCA to handle full-scale research studies.
This supplementary text is appropriate for any graduate-level, intermediate, or advanced statistics course across the social and behavioral sciences, as well as for individual researchers.
Learn more about "The Little Green Book" - QASS Series! Click Here
Requiring no prior knowledge of correspondence analysis, this text provides a nontechnical introduction to Multiple Correspondence Analysis (MCA) as a method in its own right. The authors, Brigitte LeRoux and Henry Rouanet, present thematerial in a practical manner, keeping the needs of researchers foremost in mind.
Key Features
- Readers learn how to construct geometric spaces from relevant data, formulate questions of interest, and link statistical interpretation to geometric representations.
- They also learn how to perform structured data analysis and to draw inferential conclusions from MCA.
- The text uses real examples to help explain concepts.
- The authors stress the distinctive capacity of MCA to handle full-scale research studies.
This supplementary text is appropriate for any graduate-level, intermediate, or advanced statistics course across the social and behavioral sciences, as well as for individual researchers.
Learn more about "The Little Green Book" - QASS Series! Click Here
