Regression : linear models in statistics
 Responsibility
 N.H. Bingham, John M. Fry.
 Language
 English.
 Imprint
 London ; New York : Springer, c2010.
 Physical description
 xiii, 284 p. : ill. ; 24 cm.
 Series
 Springer undergraduate mathematics series.
Access
Available online
Math & Statistics Library
Stacks
Call number  Status 

QA278.2 .B56 2010  Unknown 
More options
Creators/Contributors
 Author/Creator
 Bingham, N. H.
 Contributor
 Fry, John M. (John Michael), 1980
Contents/Summary
 Bibliography
 Includes bibliographical references and index.
 Contents

 Linear Regression. The Analysis of Variance (ANOVA). Multiple Regression. Further Multilinear Regression. Adding additional covariates and the Analysis of Covariance. Linear Hypotheses. Model Checking and Transformation of Data. Generalised Linear Models. Other topics.
 (source: Nielsen Book Data)
 Publisher's Summary
 Regression is the branch of Statistics in which a dependent variable of interest is modelled as a linear combination of one or more predictor variables, together with a random error. The subject is inherently two or higher dimensional, thus an understanding of Statistics in one dimension is essential. Regression: Linear Models in Statistics fills the gap between introductory statistical theory and more specialist sources of information. In doing so, it provides the reader with a number of worked examples, and exercises with full solutions. The book begins with simple linear regression (one predictor variable), and analysis of variance (ANOVA), and then further explores the area through inclusion of topics such as multiple linear regression (several predictor variables) and analysis of covariance (ANCOVA). The book concludes with special topics such as nonparametric regression and mixed models, time series, spatial processes and design of experiments. Aimed at 2nd and 3rd year undergraduates studying Statistics, Regression: Linear Models in Statistics requires a basic knowledge of (onedimensional) Statistics, as well as Probability and standard Linear Algebra. Possible companions include John Haigh's Probability Models, and T. S. Blyth & E.F. Robertsons' Basic Linear Algebra and Further Linear Algebra.
(source: Nielsen Book Data)
Subjects
Bibliographic information
 Publication date
 2010
 Series
 Springer undergraduate mathematics series, 16152085
 ISBN
 9781848829688 (pbk.)
 184882968X (pbk.)
 9781848829695 (eISBN)
 1848829698 (eISBN)
 Publisher Number
 12637171