GEORGE E. P. BOX, PhD, is Ronald Aylmer Fisher Professor Emeritus of Statistics and Industrial Engineering at the University of Wisconsin, Madison. His lifelong work has defined statistical analysis, while his name and research is a part of some of the most influential statistical constructs, including Box & Jenkins models, Box & Cox transformations, and Box & Behnken designs. Dr. Box is the coauthor of a number of Wiley books, including most recently, Statistical Control by Monitoring and Adjustment, Second Edition; Response Surfaces, Mixtures, and Ridge Analyses, Second Edition; and Improving Almost Anything: Ideas and Essays, Revised Edition. NORMAN R. DRAPER is professor emeritus at the University of Wisconsin, Madison, in the Department of Statistics. His research interests include Experimental Design, Linear Models, and Nonlinear Estimation.

• Nature of Bayesian Inference. Standard Normal Theory Inference Problems. Bayesian Assessment of Assumptions: Effect of Non-Normality onInferences About a Population Mean with Generalizations. Bayesian Assessment of Assumptions: Comparison of Variances. Random Effect Models. Analysis of Cross Classification Designs. Inference About Means with Information from More than One Source:One-Way Classification and Block Designs. Some Aspects of Multivariate Analysis. Estimation of Common Regression Coefficients. Transformation of Data. Tables. References. Indexes.

GEORGE E. P. BOX, PhD, is Ronald Aylmer Fisher Professor Emeritus of Statistics and Industrial Engineering at the University of Wisconsin, Madison. His lifelong work has defined statistical analysis, while his name and research is a part of some of the most influential statistical constructs, including Box & Jenkins models, Box & Cox transformations, and Box & Behnken designs. Dr. Box is the coauthor of a number of Wiley books, including most recently, Statistical Control by Monitoring and Adjustment, Second Edition; Response Surfaces, Mixtures, and Ridge Analyses, Second Edition; and Improving Almost Anything: Ideas and Essays, Revised Edition. NORMAN R. DRAPER is professor emeritus at the University of Wisconsin, Madison, in the Department of Statistics. His research interests include Experimental Design, Linear Models, and Nonlinear Estimation.

• Nature of Bayesian Inference. Standard Normal Theory Inference Problems. Bayesian Assessment of Assumptions: Effect of Non-Normality onInferences About a Population Mean with Generalizations. Bayesian Assessment of Assumptions: Comparison of Variances. Random Effect Models. Analysis of Cross Classification Designs. Inference About Means with Information from More than One Source:One-Way Classification and Block Designs. Some Aspects of Multivariate Analysis. Estimation of Common Regression Coefficients. Transformation of Data. Tables. References. Indexes.

GEORGE E. P. BOX, PhD, is Ronald Aylmer Fisher Professor Emeritus of Statistics and Industrial Engineering at the University of Wisconsin, Madison. His lifelong work has defined statistical analysis, while his name and research is a part of some of the most influential statistical constructs, including Box & Jenkins models, Box & Cox transformations, and Box & Behnken designs. Dr. Box is the coauthor of a number of Wiley books, including most recently, Statistical Control by Monitoring and Adjustment, Second Edition; Response Surfaces, Mixtures, and Ridge Analyses, Second Edition; and Improving Almost Anything: Ideas and Essays, Revised Edition. NORMAN R. DRAPER is professor emeritus at the University of Wisconsin, Madison, in the Department of Statistics. His research interests include Experimental Design, Linear Models, and Nonlinear Estimation.

• Nature of Bayesian Inference. Standard Normal Theory Inference Problems. Bayesian Assessment of Assumptions: Effect of Non-Normality onInferences About a Population Mean with Generalizations. Bayesian Assessment of Assumptions: Comparison of Variances. Random Effect Models. Analysis of Cross Classification Designs. Inference About Means with Information from More than One Source:One-Way Classification and Block Designs. Some Aspects of Multivariate Analysis. Estimation of Common Regression Coefficients. Transformation of Data. Tables. References. Indexes.