Description: Regression : Linear Models in Statistics, Paperback by Bingham, N. H.; Fry, John M., ISBN 184882968X, ISBN-13 9781848829688, Like New Used, Free shipping in the US 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. Th 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). Th concludes with special topics such as non-parametric 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 (one-dimensional) Statistics, as well as Probability and standard Linear Algebra. Possible companions include John Haigh’s Probability Models, and T. S. Blyth & . Robertsons’ Basic Linear Algebra and Further Linear Algebra.
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Book Title: Regression : Linear Models in Statistics
Number of Pages: Xiii, 284 Pages
Language: English
Publication Name: Regression : Linear Models in Statistics
Publisher: Springer London, The Limited
Publication Year: 2010
Subject: Probability & Statistics / Regression Analysis, Probability & Statistics / General, Applied
Item Weight: 33.2 Oz
Type: Textbook
Subject Area: Mathematics
Author: N. H. Bingham, John M. Fry
Item Length: 9.3 in
Series: Springer Undergraduate Mathematics Ser.
Item Width: 6.1 in
Format: Trade Paperback
