Applied Regression Analysis (2nd Ed., 2nd Corrected ed. 1998. Corr. 2nd printing 2001) A Research Tool Springer Texts in Statistics Series
Auteurs : Rawlings John O., Pantula Sastry G., Dickey David A.
Applied Regression Analysis is aimed at the scientist who wishes to gain a working knowledge of regression analysis. The basic purpose of this book is to develop an understanding of least squares and related statistical methods without becoming excessively mathematical. It is the outgrowth of more than 30 years of consulting experience with scientists and many years of teaching an applied regression course to graduate students. Applied Regression Analysis serves as an excellent text for a service course on regression for non-statisticians and as a reference for researchers. It also provides a bridge between a two-semester introduction to statistical methods and a thoeretical linear models course.
Applied Regression Analysis emphasizes the concepts and the analysis of data sets. It provides a review of the key concepts in simple linear regression, matrix operations, and multiple regression. Methods and criteria for selecting regression variables and geometric interpretations are discussed. Polynomial, trigonometric, analysis of variance, nonlinear, time series, logistic, random effects, and mixed effects models are also discussed. Detailed case studies and exercises based on real data sets are used to reinforce the concepts. The data sets used in the book are available on the Internet.
Date de parution : 03-2013
Ouvrage de 660 p.
17.8x25.4 cm
Disponible chez l'éditeur (délai d'approvisionnement : 15 jours).
Prix indicatif 89,66 €
Ajouter au panierDate de parution : 04-2001
Ouvrage de 660 p.
17.8x25.4 cm
Thème d’Applied Regression Analysis :
Mots-clés :
Analysis of variance; Excel; Regression analysis; SAS; STATISTICA; Time series; linear regression