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This book blends theory and applications, reinforcing concepts with practical real-world examples that illustrate the importance of probability to those who will use it in their subsequent courses and careers. The author emphasizes the study of probability distributions that characterize random variables, because this knowledge is essential in performing parametric statistical analysis. Explanations include the "why" as well as the "how" of probability distributions for random variables to help engage readers and further promote their understanding. In addition, the text includes a self-contained chapter on finite Markov chains, which introduces the basic aspects of Markov chains and illustrates their usefulness with several real examples.
Decision Information is a collection of manuscripts presented at the 1976 Workshop on Decision Information for Tactical Command and Control, held at the Airlie House in Airlie, Virginia. This workshop provides the scientific managers of the Service Office of Research with the knowledge allowing them to formulate research programs relevant to military problems in decision information. This book is organized into three parts encompassing 28 chapters. The first part consists of presentations in systems approach to large-scale human and man-machine systems, benefit-cost models for decision makers, team decision models, and cubic interpolation processes. The contributors highlight the various the...
The Joy of Finite Mathematics: The Language and Art of Math teaches students basic finite mathematics through a foundational understanding of the underlying symbolic language and its many dialects, including logic, set theory, combinatorics (counting), probability, statistics, geometry, algebra, and finance. Through detailed explanations of the concepts, step-by-step procedures, and clearly defined formulae, readers learn to apply math to subjects ranging from reason (logic) to finance (personal budget), making this interactive and engaging book appropriate for non-science, undergraduate students in the liberal arts, social sciences, finance, economics, and other humanities areas. The author...
This book contains entirely new results, not to be found elsewhere. Furthermore, additional results scattered elsewhere in the literature are clearly presented. Several well-known distributions such as Weibull distributions, exponentiated Burr type XII distributions and exponentiated exponential distributions and their properties are demonstrated. Analysis of real as well as well-simulated data are analyzed. A number of inferences based on a finite mixture of distributions are also presented.
Topics emphasized in this book include nonparametric density estimation, multi-dimensional data analysis, cancer progression, chaos theory, and parallel based algorithms.
A lot of statisticians, actuarial mathematicians, reliability engineers, meteorologists, hydrologists, economists. Business and sport analysts deal with records which play important roles in various fields of statistics and its application. This book enables a reader to check his/her level of understanding of the theory of record values. We give basic formulae which are more important in the theory and present a lot of examples which illustrate the theoretical statements. For a beginner in record statistics, as well as for graduate students the study of our book needs the basic knowledge of the subject. A more advanced reader can use our book to polish his/her knowledge. An upgraded list of bibliography which will help a reader to enrich his/her theoretical knowledge and widen the experience of dealing with ordered observations, is also given in the book.
Provides in an organized manner characterizations of univariate probability distributions with many new results published in this area since the 1978 work of Golambos & Kotz "Characterizations of Probability Distributions" (Springer), together with applications of the theory in model fitting and predictions.
The most important properties of normal and Student t-distributions are presented. A number of applications of these properties are demonstrated. New related results dealing with the distributions of the sum, product and ratio of the independent normal and Student distributions are presented. The materials will be useful to the advanced undergraduate and graduate students and practitioners in the various fields of science and engineering.
Ordered Random Variables have attracted several authors. The basic building block of Ordered Random Variables is Order Statistics which has several applications in extreme value theory and ordered estimation. The general model for ordered random variables, known as Generalized Order Statistics has been introduced relatively recently by Kamps (1995).