Includes bibliographical references and index

Introduction -- Some key ideas -- Experimental strategies -- The choice of a model -- Models and least squares -- Criteria for a good experiment -- Standard designs -- The analysis of experiments -- Optimum design theory -- Criteria of optimality -- D-optimum designs -- Algorithms for the construction of exact D-optimum designs -- Optimum experimental design with SAS -- Experiments with both qualitative and quantitative factors -- Blocking response surface designs -- Mixture experiments -- Non-linear models -- Bayesian optimum designs -- Design augmentation -- Model checking and designs for discriminating between models -- Compound design criteria -- Generalized linear models -- Response transformation and structured variances -- Time-dependent models with correlated observations -- Further topics -- Exercises