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Linear Model Methodology
Given the importance of linear models in statistical theory and experimental research, a good understanding of their fundamental principles and theory is essential. Supported by a large number of examples, Linear Model Methodology provides a strong foundation in the theory of linear models and explores the latest developments in data analysis.After
Advanced Calculus with Applications in Statistics
Successful track record No competition Unique blend of mathematics and statistics Emphasis on applications
Matrix Algebra Useful for Statistics
A thoroughly updated guide to matrix algebra and it uses in statistical analysis and features SAS®, MATLAB®, and R throughout This Second Edition addresses matrix algebra that is useful in the statistical analysis of data as well as within statistics as a whole. The material is presented in an explanatory style rather than a formal theorem-proof format and is self-contained. Featuring numerous applied illustrations, numerical examples, and exercises, the book has been updated to include the use of SAS, MATLAB, and R for the execution of matrix computations. In addition, André I. Khuri, who has extensive research and teaching experience in the field, joins this new edition as co-author. Th...
Design and Analysis of Experiments
"The eighth edition of Design and Analysis of Experiments continues to provide extensive and in-depth information on engineering, business, and statistics-as well as informative ways to help readers design and analyze experiments for improving the quality, efficiency and performance of working systems. Furthermore, the text maintains its comprehensive coverage by including: new examples, exercises, and problems (including in the areas of biochemistry and biotechnology); new topics and problems in the area of response surface; new topics in nested and split-plot design; and the residual maximum likelihood method is now emphasized throughout the book"--
