Sprache: Englisch
Verlag: SAGE Publications, Inc (edition 1), 1977
ISBN 10: 0803906552 ISBN 13: 9780803906556
Anbieter: BooksRun, Philadelphia, PA, USA
Paperback. Zustand: Very Good. 1. It's a well-cared-for item that has seen limited use. The item may show minor signs of wear. All the text is legible, with all pages included. It may have slight markings and/or highlighting.
Zustand: Good. Good condition. A copy that has been read but remains intact. May contain markings such as bookplates, stamps, limited notes and highlighting, or a few light stains.
Paperback. Zustand: Very Good. No Jacket. May have limited writing in cover pages. Pages are unmarked. ~ ThriftBooks: Read More, Spend Less.
Sprache: Englisch
Verlag: SAGE Publications, Incorporated, 1977
ISBN 10: 0803906552 ISBN 13: 9780803906556
Anbieter: Better World Books, Mishawaka, IN, USA
Zustand: Good. Former library copy. Pages intact with minimal writing/highlighting. The binding may be loose and creased. Dust jackets/supplements are not included. Includes library markings. Stock photo provided. Product includes identifying sticker. Better World Books: Buy Books. Do Good.
Anbieter: Mythos Center Books, Frontenac, MN, USA
Paperback. Zustand: Used: Very Good. 11th printing. Softcover, 62p, VG. Series: Quantitative Applications in the Social Sciences.
Broschiert. Zustand: Gut. 62 Seiten; Das hier angebotene Buch stammt aus einer teilaufgelösten Bibliothek und kann die entsprechenden Kennzeichnungen aufweisen (Rückenschild, Instituts-Stempel.); der Buchzustand ist ansonsten ordentlich und dem Alter entsprechend gut. In ENGLISCHER Sprache. Sprache: Englisch Gewicht in Gramm: 90.
Anbieter: Revaluation Books, Exeter, Vereinigtes Königreich
EUR 76,36
Anzahl: 2 verfügbar
In den WarenkorbPaperback. Zustand: Brand New. 64 pages. 8.75x5.50x0.25 inches. In Stock.
Anbieter: Buchpark, Trebbin, Deutschland
Zustand: Gut. Zustand: Gut | Sprache: Englisch | Produktart: Bücher | An advanced study which presumes a knowledge of multiple regression and factor analysis techniques, this paper considers two techniques for comparing entire sets of data, and develops the canonical correlation model as an extension of regression analysis in which there are several dependent variables.