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Probability Theory and Mathematical Statistics for Engineers

Probability Theory and Statistical Methods for Engineers brings together probability theory with the more practical applications;

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Probability Theory and Mathematical Statistics for Engineers

Probability Theory and Statistical Methods for Engineers brings together probability theory with the more practical applications;

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Statistics in the 21st Century

sections: statistics in the life and medical sciences, business and social science, the physical sciences and engineering, and theory and methods;

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Robust Statistics

, thus increasing the reliability of fitted models and associated inference. This new, second edition of Robust Statistics: Theory and Methods;

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Statistics and Analysis of Scientific Data

Statistics and Analysis of Scientific Data covers the foundations of probability theory and statistics, and a number of numerical and;

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Functional Methods in Quantum Field Theory and Statistical Physics

formulation, relativistic quantum field theory, Euclidean field theory, quantum statistics at finite temperature, and the classical statistics;

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Functional Methods in Quantum Field Theory and Statistical Physics

formulation, relativistic quantum field theory, Euclidean field theory, quantum statistics at finite temperature, and the classical statistics;

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Statistics in Musicology

analysis, music theory, and performance theory. It explores concrete methods for data generation and numerical encoding of musical data and serves;

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Applied Statistics

theory and the application of modern statistical and mathematical modelling techniques to applied problems in industry, public services, commerce;

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Statistics and Analysis of Scientific Data

Statistics and Analysis of Scientific Data covers the foundations of probability theory and statistics, and a number of numerical;

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Mathematical Statistics with Applications in R

, Metropolis-Hastings algorithm and the Gibbs sampler. By combining discussion on the theory of statistics with a wealth of real-world applications;

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Nonlinear Dynamics and Statistics

Isaac Newton Institute, Cambridge University, UK, in late 1998. The book's chapters present theory and methods topics by leading researchers;

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Statistical Methods for Business and Economics

descriptive statistics, probability, sample theory and inferential statistics, taking students from the basics through to more advanced topics such as;

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Statistics

numbers - Sampling theory and inference; - offers complete coverage of introductory professional and academic courses on statistics and;

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Elements of Statistical Computing

Statistics and computing share many close relationships. Computing now permeates every aspect of statistics, from pure description to the;

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Mathematical Statistics

theory. This edition gives careful proofs of major results and explains how the theory sheds light on the properties of practical methods;

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Basic Statistics for Social Research

, independence, correlation and regression. The use of math and theory are deliberately limited, and the authors focus on how the concepts and tools;

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Course in Mathematical Statistics and Large Sample Theory

mathematical statistics. Part II deals with the large sample theory of statistics - parametric and nonparametric, and its contents may be covered;

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Statistics for Technology

Introduction describes some simple methods of summarizing data. Theory examines the basic concepts and theory of statistics. Applications covers the;

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Statistics for Technology

Introduction describes some simple methods of summarizing data. Theory examines the basic concepts and theory of statistics. Applications covers the;

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Theory And Applications Of Recent Robust Methods

methods. It contains up-to-date research results in the theory of robust statistics Treats computational aspects and algorithms and shows;

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Bayesian Statistics for Experimental Scientists

statistics. The book first covers elementary probability theory, the binomial model, the multinomial model, and methods for comparing different;

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Insight into Statistics

A must insight into statistics for Social Sciences. It is a comprehensive introduction to probability theory and statistical methods in the;

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Mathematical Statistics

that form the basis of modern statistics, and examines the foundations of estimation theory, hypothesis testing theory and statistical game;

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An introduction to mathematical statistics

theory, calculus, and linear algebra.;

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Introductory Mathematics And Statistics For Islamic Finance

research, the book provides readers with the working knowledge of math and statistics required to understand Islamic finance theory and practice;

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Principles and Theory for Data Mining and Machine Learning

Extensive treatment of the most up-to-date topics Provides the theory and concepts behind popular and emerging methods Range of topics;

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