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1. |
Record Nr. |
UNISALENTO991000658889707536 |
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Autore |
Abhyankar, Shreeram Shankar |
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Titolo |
Algebraic geometry and its applications : collections of papers from Shreeram S. Abhyankar's 60th birthday conference / Chandrajit L. Bajaj, editor |
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Pubbl/distr/stampa |
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New York : Springer-Verlag, c1994 |
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ISBN |
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Descrizione fisica |
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xxii, 536 p. : ill. ; 25 cm. |
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Classificazione |
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AMS 13-06 |
AMS 14-06 |
QA564.A355 |
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Altri autori (Persone) |
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Disciplina |
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Soggetti |
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Algebraic geometry - Congresses |
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Lingua di pubblicazione |
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Formato |
Materiale a stampa |
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Livello bibliografico |
Monografia |
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Note generali |
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Includes bibliographical references |
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2. |
Record Nr. |
UNINA9910367254203321 |
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Autore |
Roni Saiyidi Mat |
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Titolo |
Conducting quantitative research in education / / Saiyidi Mat Roni, Margaret Kristin Merga, Julia Elizabeth Morris |
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Pubbl/distr/stampa |
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Singapore : , : Springer Singapore : , : Imprint : Springer, , [2020] |
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©2020 |
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ISBN |
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Edizione |
[1st edition 2020.] |
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Descrizione fisica |
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1 online resource (viii, 201 pages) : illustrations |
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Disciplina |
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Soggetti |
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Management - Study and teaching |
Big data |
Statistics |
Management Education |
Big Data/Analytics |
Statistics for Social Sciences, Humanities, Law |
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Lingua di pubblicazione |
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Formato |
Materiale a stampa |
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Livello bibliografico |
Monografia |
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Nota di bibliografia |
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Includes bibliographical references and index. |
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Nota di contenuto |
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Introduction -- Getting started: What, where, why -- Conducting research with children and students -- Data types and samples -- Data preparation -- Analysis: Difference between groups -- Analysis: Correlation -- Analysis: Regression -- Write up and research translation -- Conclusion and further reading. |
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Sommario/riassunto |
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This book provides a clear and straightforward guide for all those seeking to conduct quantitative research in the field of education, using primary research data samples. While positioned as less powerful and somehow inferior, non-parametric tests can be very useful where the research can only be designed to accommodate data structure which is ordinal, or scale but violates a normality assumption, which is required for parametric tests. Non-parametric data are a staple of educational research, and as such, it is essential that educational researchers learn how to work with these data with confidence and rigour. |
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