Parametri
- 720pagine
- 26 ore di lettura
Maggiori informazioni sul libro
This best-selling text is written for those who use, rather than develop, advanced statistical methods. Dr. Stevens focuses on a conceptual understanding of the material rather than proving results. Helpful narrative and numerous examples enhance understanding, and a chapter on matrix algebra serves as a review. Printouts from SPSS and SAS with annotations indicate what the numbers mean and encourage interpretation of the results. In addition to demonstrating how to use the packages effectively, the author stresses the importance of checking the data, assessing the assumptions, and ensuring adequate sample size (by providing guidelines) so that the results can be generalized. The new edition features a CD-ROM with the data sets and many new exercises. Ideal for courses on advanced or multivariate statistics found in psychology, education, and business departments, the book also appeals to practicing researchers with little or no training in multivariate methods. Prerequisites include a course on factorial analysis of variance. It does not assume a working knowledge of matrix algebra.
Acquisto del libro
Applied Multivariate Statistics for the Social Sciences, James P Stevens
- Lingua
- Pubblicato
- 2002
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- (In brossura),
- Condizioni del libro
- In buone condizioni
- Prezzo
- 6,99 €
Metodi di pagamento
Ancora nessuna valutazione.
- Titolo
- Applied Multivariate Statistics for the Social Sciences
- Sottotitolo
- Fourth Edition
- Lingua
- Inglese
- Autori
- James P Stevens
- Editore
- Psychology Press
- Pubblicato
- 2002
- Formato
- In brossura
- Pagine
- 720
- ISBN10
- 0805837779
- ISBN13
- 9780805837773
- Serie
- Tag
- Saggistica, Scienze sociali, Libri di testo, Commercio, Business & Management, Temi psicologici, Altri libri di testo, Psicologia, Libri di testo di matematica
- Descrizione
- This best-selling text is written for those who use, rather than develop, advanced statistical methods. Dr. Stevens focuses on a conceptual understanding of the material rather than proving results. Helpful narrative and numerous examples enhance understanding, and a chapter on matrix algebra serves as a review. Printouts from SPSS and SAS with annotations indicate what the numbers mean and encourage interpretation of the results. In addition to demonstrating how to use the packages effectively, the author stresses the importance of checking the data, assessing the assumptions, and ensuring adequate sample size (by providing guidelines) so that the results can be generalized. The new edition features a CD-ROM with the data sets and many new exercises. Ideal for courses on advanced or multivariate statistics found in psychology, education, and business departments, the book also appeals to practicing researchers with little or no training in multivariate methods. Prerequisites include a course on factorial analysis of variance. It does not assume a working knowledge of matrix algebra.