\u003cp\u003e\u003cb\u003eExplores mathematical statistics in its entirety--from the fundamentals to modern methods\u003c/b\u003e\u003c/p\u003e \u003cp\u003eThis book introduces readers to point estimation, confidence intervals, and statistical tests. Based on the general theory of linear models, it provides an in-depth overview of the following: analysis of variance (ANOVA) for models with fixed, random, and mixed effects; regression analysis is also first presented for linear models with fixed, random, and mixed effects before being expanded to nonlinear models; statistical multi-decision problems like statistical selection procedures (Bechhofer and Gupta) and sequential tests; and design of experiments from a mathematical-statistical point of view. Most analysis methods have been supplemented by formulae for minimal sample sizes. The chapters also contain exercises with hints for solutions.\u003c/p\u003e \u003cp\u003eTranslated from the successful German text, \u003ci\u003eMathematical Statistics\u003c/i\u003e requires knowledge of probability theory (combinatorics, probability distributions, functions and sequences of random variables), which is typically taught in the earlier semesters of scientific and mathematical study courses. It teaches readers all about statistical analysis and covers the design of experiments. The book also describes optimal allocation in the chapters on regression analysis. Additionally, it features a chapter devoted solely to experimental designs.\u003c/p\u003e \u003cul\u003e \u003cli\u003eClassroom-tested with exercises included\u003c/li\u003e \u003cli\u003ePractice-oriented (taken from day-to-day statistical work of the authors)\u003c/li\u003e \u003cli\u003eIncludes further studies including design of experiments and sample sizing\u003c/li\u003e \u003cli\u003ePresents and uses IBM SPSS Statistics 24 for practical calculations of data\u003c/li\u003e \u003c/ul\u003e \u003cp\u003e\u003ci\u003eMathematical Statistics\u003c/i\u003e is a recommended text for advanced students and practitioners of math, probability, and statistics.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e
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