An exploration of the interelated fields of design of experiments and sequential analysis.
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Preliminaries on probability; Generalities about the conventional theory of design of experiments; Optimal sample size; Preliminaries on regression; Design for linear regression: Elfving's method; Maximum-likelihood estimation; Locally optimal designs for estimation; More design in regression experiments; Testing hypotheses; Optimal sample size in testing; Sequential probability-ratio test; Optimality of sequential probability-ratio test; Motivation for an approach to sequential design of experiments in testing hypotheses; Asymptotic optimality of procedure A in sequential design; Extensions and open questions in sequential design; The problem of adjacent hypotheses; Testing for the sign of a normal mean: no indifference zone; Bandit problems; Sequential estimation of a normal mean; sequential estimation of the common mean of two normal populations.
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