Applied Multivariate Data Analysis : Regression and Experimental Design [Vol. I ] / J. D. Jobson

By:

Jobson, J. D

9780387976600

Subject(s):

DDC classification:

519.5 JobA

Summary: An easy to read survey of data analysis, linear regression models and analysis of variance. The extensive development of the linear model includes the use of the linear model approach to analysis of variance provides a strong link to statistical software packages, and is complemented by a thorough overview of theory. It is assumed that the reader has the background equivalent to an introductory book in statistical inference. Can be read easily by those who have had brief exposure to calculus and linear algebra. Intended for first year graduate students in business, social and the biological sciences. Provides the student with the necessary statistics background for a course in research methodology. In addition, undergraduate statistics majors will find this text useful as a survey of linear models and their applications

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Item type	Current library	Collection	Call number	Status	Barcode
Books	Indian Institute of Technology Tirupati General Stacks	Mathematics	519.5 JobA (12198) (Browse shelf(Opens below))	Available	12198

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Previous	519.5 HOL Nonparametric Statistical Methods /	519.5 HolN3 Nonparametric Statistical Methods /	519.5 JIA/L Linear and Generalized Linear Mixed Models and their Applications	519.5 JobA (12198) Applied Multivariate Data Analysis : Regression and Experimental Design [Vol. I ] /	519.5 JOH BASIC EXPERIMENTAL STRATEGIES AND DATA ANALYSIS FOR SCIENCE AND ENGINEERING	519.5 KarR Reliability and Survival Analysis /	519.5 LeeU (09829) U-Statistics : Theory and Practice /	Next

An easy to read survey of data analysis, linear regression models and analysis of variance. The extensive development of the linear model includes the use of the linear model approach to analysis of variance provides a strong link to statistical software packages, and is complemented by a thorough overview of theory. It is assumed that the reader has the background equivalent to an introductory book in statistical inference. Can be read easily by those who have had brief exposure to calculus and linear algebra. Intended for first year graduate students in business, social and the biological sciences. Provides the student with the necessary statistics background for a course in research methodology. In addition, undergraduate statistics majors will find this text useful as a survey of linear models and their applications

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