Data analysis : a model comparison approach / M. Judd Charles, Gary H. McClelland, Carey S. Ryan
Tipo de material: TextoDetalles de publicación: New York : Routledge, 2009 Edición: 2nd ed.Descripción: XII, 328 p. : gráf. ; 26 cmISBN: 978-0-8058-3388-1Tema(s): Análisis multivariante | Estadística matemática | EstadísticaResumen: This completely rewritten classic text features many new examples, insights and topics including mediational, categorical, and multilevel models. Substantially reorganized, this edition provides a briefer, more streamlined examination of data analysis. Noted for its model-comparison approach and unified framework based on the general linear model, the book provides readers with a greater understanding of a variety of statistical procedures. This consistent framework, including consistent vocabulary and notation, is used throughout to develop fewer but more powerful model building techniques. The authors show how all analysis of variance and multiple regression can be accomplished within this framework.Tipo de ítem | Biblioteca de origen | Signatura | URL | Estado | Fecha de vencimiento | Código de barras | Reserva de ítems |
---|---|---|---|---|---|---|---|
Monografías | 02. BIBLIOTECA CAMPUS PUERTO REAL | 519.2/JUD/dat (Navegar estantería(Abre debajo)) | Texto completo | Disponible Ubicación en estantería | Bibliomaps® | 3743046035 |
Índice
This completely rewritten classic text features many new examples, insights and topics including mediational, categorical, and multilevel models. Substantially reorganized, this edition provides a briefer, more streamlined examination of data analysis. Noted for its model-comparison approach and unified framework based on the general linear model, the book provides readers with a greater understanding of a variety of statistical procedures. This consistent framework, including consistent vocabulary and notation, is used throughout to develop fewer but more powerful model building techniques. The authors show how all analysis of variance and multiple regression can be accomplished within this framework.
No hay comentarios en este titulo.