Presenting an integrated approach to Statistical Inference at a graduate level, this book discusses and compares the two main schools of statistical thought: frequentist and Bayesian. It covers such subjects as point and interval estimation, hypotheses testing and prediction, while also exploring recent computationally-intensive methods. "Statistical Inference" ideally compliments "Bayesian Statistics" and "Kendall's Advanced Theory of Statistics, Volumes 1, 2A" and "2B". It will prove invaluable to postgraduates in the fields of statistics, operations research, mathematics and economics. Applied statisticians will also find it a useful reference tool and a source of information on newer developments.
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