1.

Record Nr.

UNINA990003984580403321

Autore

Armstrong, John M.

Titolo

Coastal waters : A Management Analysis / John M. Armstrong, Peter C. Rymer

Pubbl/distr/stampa

Michigan : Ann Arbor Science, 1978

ISBN

0-250-40238-6

Descrizione fisica

V, 240 p. ; 25 cm

Locazione

DINID

DMIGI

Collocazione

15 G/1-20

IG 15 D 26

Lingua di pubblicazione

Inglese

Formato

Materiale a stampa

Livello bibliografico

Monografia

Note generali

Bibl. Ing. Sanitaria



2.

Record Nr.

UNISALENTO991003445429707536

Autore

International Colloquium for Origen Studies <5. ; 1989 ; Boston College>

Titolo

Origeniana quinta : historica, text and method, biblica, philosophica, theologica, Origenism and later developments : papers of the 5th International Origen Congress, Boston College, 14-18 August 1989 / edited by Robert J. Daly

Pubbl/distr/stampa

Leuven : University Press : Peeters, 1992

ISBN

9061865115 (Leuven University Press)

9068314238 (Uitgeverij Peeters)

Descrizione fisica

XVII, 635 p. ; 25 cm

Collana

Bibliotheca ephemeridum theologicarum Lovaniensium ; 105

Altri autori (Persone)

Daly, Robert J.

Soggetti

Origene Congressi

Origene Congressi

Lingua di pubblicazione

Tedesco

Italiano

Inglese

Francese

Spagnolo

Formato

Materiale a stampa

Livello bibliografico

Monografia

Nota di bibliografia

Contiene riferimenti bibliografici. indici



3.

Record Nr.

UNINA9910709771903321

Autore

Beede David N.

Titolo

Women in STEM: a gender gap to innovation / / by David Beede [and five others]

Pubbl/distr/stampa

Washington, DC : , : U.S. Department of Commerce, Economics and Statistics Administration, , 2011

Descrizione fisica

1 online resource (11 pages) : color illustrations

Collana

ESA issue brief ; ; #11-04

Soggetti

Women in science - United States

Women in technology - United States

Women in engineering - United States

Women in mathematics - United States

Statistics.

Lingua di pubblicazione

Inglese

Formato

Materiale a stampa

Livello bibliografico

Monografia

Note generali

"August 2011."



4.

Record Nr.

UNINA9910826557703321

Autore

Brown Bruce (Bruce L.)

Titolo

Multivariate analysis for the biobehavioral and social sciences / / Bruce L. Brown, ... [et al.]

Pubbl/distr/stampa

Hoboken, N.J., : Wiley, c2012

ISBN

9786613332257

9781283332255

1283332256

9781118131626

1118131622

9781118131619

1118131614

9781118131596

1118131592

Edizione

[1st ed.]

Descrizione fisica

1 online resource (xiv, 475 pages) : illustrations

Classificazione

MAT029020

Disciplina

300.1/519535

Soggetti

Social sciences - Statistical methods

Multivariate analysis

Lingua di pubblicazione

Inglese

Formato

Materiale a stampa

Livello bibliografico

Monografia

Note generali

Description based upon print version of record.

Nota di bibliografia

Includes bibliographical references and index.

Nota di contenuto

Overview of Multivariate and Regression Methods -- The Seven Habits of Highly Effective Quants: A Review of Elementary Statistics Using Matrix Algebra -- Fundamentals of Matrix Algebra -- Factor Analysis and Related Methods: Quintessentially Multivariate -- Multivariate Graphics -- Canonical Correlation: The Underused Method -- Hotelling's as the Simplest Case of Multivariate Inference -- Multivariate Analysis of Variance -- Multiple Regression and the General Linear Model -- Appendices: Statistical Tables -- Name Index -- Subject Index.

Sommario/riassunto

Multivariate Analysis for the Social Sciences provides clear guidelines combined with the insight needed to understand the methods and applications of multivariate statistics. This easy-to-follow book provides students in social, behavioral, and health science-whose focus



is not primarily in mathematics-with an abundance of chapter-ending questions and answers, including: conceptual questions about the meaning of each method; questions that test the reader's ability to carry out the computational procedures on simple datasets; and data analysis questions for using analytical packages to analyze both simplest case data and also to practice with more realistic datasets.