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Methods and Applications of Linear Models: Regression and the Analysis of Variance, Second Edition
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More About This Title Methods and Applications of Linear Models: Regression and the Analysis of Variance, Second Edition

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RONALD R. HOCKING, PhD, is Professor Emeritus in the Department of Statistics at Texas A&M University. He is also co-owner of PenHock Statistical Consultants in Ishpeming, Michigan.
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Preface to the Second Edition.

Preface to the First Edition.

PART I: REGRESSION MODELS.

Introduction to Linear Models.

Regression on Functions of One Variable.

Transforming the Data.

Regression of Functions of Several Variables.

Collinearity in Multiple Linear Regression.

Influential Observations in Multiple Linear Regression.

Polynomial Models and Qualitative Predictors.

Additional Topics.

PART II: ANALYSIS OF VARIANCE MODELS.

Introduction to Analysis of Variance Models.

Fixed Effects Models I: One-Way Classification of Means.

Fixed Effects Models II: Two-Way Classification of Means.

Fixed Effects Models III: Multiple Crossed and Nested Factors.

Mixed Models I: The AOV Method with Balanced Data.

Mixed Models II: The AVE Method with Balanced Data.

Mixed Models III: Unbalanced Data.

PART III: MATHEMATICAL THEORY OF LINEAR MODELS.

Distribution of Linear and Quadratic Forms.

Estimation and Inference for Linear Models.

Simultaneous Inference: Tests and Confidence Intervals .

Appendix A. Mathematics.

Appendix B. Statistics.

Appendix C. Statistical Tables.

Appendix D. Data Tables.

References.

Index.

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“...presents a thorough treatment of the concepts and methods of linear model analysis and illustrates them with numerical and conceptual examples...” (Quarterly of Applied Mathematics, Vol. LXII, No. 1, March 2004)

"...an essential desktop reference book...it should definitely be on your bookshelf." (Technometrics, Vol. 45, No. 4, November 2003)

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