Principles of Statistics
Concise description of classical statistics, from basic dice probabilities to modern regression analysis. Equal stress on theory and applications. Moderate difficulty; only basic calculus required. Includes problems with answers.
Principles of Applied Statistics
Applied statistics is more than data analysis, but it is easy to lose sight of the big picture. David Cox and Christl Donnelly distil decades of scientific experience into usable principles for the successful application of statistics, showing how good statistical strategy shapes every stage of an investigation. As you advance from research or policy question, to study design, through modelling and interpretation, and finally to meaningful conclusions, this book will be a valuable guide. Over a hundred illustrations from a wide variety of real applications make the conceptual points concrete, illuminating your path and deepening your understanding. This book is essential reading for anyone who makes extensive use of statistical methods in their work.
The Principles of Statistical Mechanics
This is the definitive treatise on the fundamentals of statistical mechanics. A concise exposition of classical statistical mechanics is followed by a thorough elucidation of quantum statistical mechanics: postulates, theorems, statistical ensembles, changes in quantum mechanical systems with time, and more. The final two chapters discuss applications of statistical mechanics to thermodynamic behavior. 1930 edition.
Principles of Statistics
Mohammad Z. Raqab A été écrit sous une forme ou une autre pendant la plus grande partie de sa vie. Vous pouvez trouver autant d'inspiration de Principles of Statistics Aussi informatif et amusant. Cliquez sur le bouton TÉLÉCHARGER ou Lire en ligne pour obtenir gratuitement le livre de titre $ gratuitement.
Principles of Statistical Inference
In this book, an integrated introduction to statistical inference is provided from a frequentist likelihood-based viewpoint. Classical results are presented together with recent developments, largely built upon ideas due to R.A. Fisher. The term ?neo-Fisherian? highlights this.After a unified review of background material (statistical models, likelihood, data and model reduction, first-order asymptotics) and inference in the presence of nuisance parameters (including pseudo-likelihoods), a self-contained introduction is given to exponential families, exponential dispersion models, generalized linear models, and group families. Finally, basic results of higher-order asymptotics are introduced (index notation, asymptotic expansions for statistics and distributions, and major applications to likelihood inference).The emphasis is more on general concepts and methods than on regularity conditions. Many examples are given for specific statistical models. Each chapter is supplemented with problems and bibliographic notes. This volume can serve as a textbook in intermediate-level undergraduate and postgraduate courses in statistical inference.
Principles of statistics
Victor E. McGee A été écrit sous une forme ou une autre pendant la plus grande partie de sa vie. Vous pouvez trouver autant d'inspiration de Principles of statistics Aussi informatif et amusant. Cliquez sur le bouton TÉLÉCHARGER ou Lire en ligne pour obtenir gratuitement le livre de titre $ gratuitement.
Principles of Statistics for Engineers and Scientists
Facts101 is your complete guide to Principles of Statistics for Engineers and Scientists. In this book, you will learn topics such as Commonly Used Distributions, Point and Interval Estimation for a Single Sample, Hypothesis Tests for a Single Sample, and Inferences for Two Samples plus much more. With key features such as key terms, people and places, Facts101 gives you all the information you need to prepare for your next exam. Our practice tests are specific to the textbook and we have designed tools to make the most of your limited study time.
Principles of statistics
Presents comprehensive coverage of statistics in a step-by-step format, geared for undergraduates majoring in the social sciences. Discusses the basic theoretical concepts of statistics. Explains how statistics are applied to research studies. Emphasizes principles, integration, and understanding rather than rules. Includes exercises taken from actual psychological research, sketches and diagrams for problem solving, techniques to estimate the approximate value of a statistic, review chapters, statistical tables, and much more.
Principles of Statistical Genomics
Statistical genomics is a rapidly developing field, with more and more people involved in this area. However, a lack of synthetic reference books and textbooks in statistical genomics has become a major hurdle on the development of the field. Although many books have been published recently in bioinformatics, most of them emphasize DNA sequence analysis under a deterministic approach. Principles of Statistical Genomics synthesizes the state-of-the-art statistical methodologies (stochastic approaches) applied to genome study. It facilitates understanding of the statistical models and methods behind the major bioinformatics software packages, which will help researchers choose the optimal algorithm to analyze their data and better interpret the results of their analyses. Understanding existing statistical models and algorithms assists researchers to develop improved statistical methods to extract maximum information from their data. Resourceful and easy to use, Principles of Statistical Genomics is a comprehensive reference for researchers and graduate students studying statistical genomics.