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Linear Model Methodology
Given the importance of linear models in statistical theory and experimental research, a good understanding of their fundamental principles and theory is essential. Supported by a large number of examples, Linear Model Methodology provides a strong foundation in the theory of linear models and explores the latest developments in data analysis.After
Advanced Calculus with Applications in Statistics
Designed to help motivate the learning of advanced calculus by demonstrating its relevance in the field of statistics, this successful text features detailed coverage of optimization techniques and their applications in statistics while introducing the reader to approximation theory. The Second Edition provides substantial new coverage of the material, including three new chapters and a large appendix that contains solutions to almost all of the exercises in the book. Applications of some of these methods in statistics are discusses.
Response Surfaces: Designs and Analyses
Response Surfaces: Designs and Analyses; Second Edition presents techniques for designing experiments that yield adequate and reliable measurements of one or several responses of interest, fitting and testing the suitability of empirical models used for acquiring information from the experiments, and for utilizing the experimental results to make decisions concerning the system under investigation. This edition contains chapters on response surface models with block effects and on Taguchi's robust parameter design, additional details on transformation of response variable, more material on modified ridge analysis, and new design criteria, including rotatability for multiresponse experiments. It also presents an innovative technique for displaying correlation among several response. Numerical examples throughout the book plus exercises--with worked solutions to selected problems--complement the text.
Response Surface Methodology and Related Topics
This is the first edited volume on response surface methodology (RSM). It contains 17 chapters written by leading experts in the field and covers a wide variety of topics ranging from areas in classical RSM to more recent modeling approaches within the framework of RSM, including the use of generalized linear models. Topics covering particular aspects of robust parameter design, response surface optimization, mixture experiments, and a variety of new graphical approaches in RSM are also included. The main purpose of this volume is to provide an overview of the key ideas that have shaped RSM, and to bring attention to recent research directions and developments in RSM, which can have many useful applications in a variety of fields. The volume will be very helpful to researchers as well as practitioners interested in RSM's theory and potential applications. It will be particularly useful to individuals who have used RSM methods in the past, but have not kept up with its recent developments, both in theory and applications.
Spray Drying for the Food Industry
Spray Drying for the Food Industry, in the Unit Operations and Processing Equipment in the Food Industry series, explains the fundamental and applied research in all aspects of spray drying from engineering to technology. The book thoroughly examines the spray drying of food materials with an emphasis on production, processing, engineering, characterization, and applications of spray dried food powders that enable novel/enhanced properties or functions. Divided into four sections, "Fundamentals of Spray drying process", "Application of spray drying for production of food powders", "Encapsulation of food bioactive ingredients by spray drying", and "Characterization and analysis of spray dried...
Introduction to Probability and Statistics, Second Edition,
Beginning with the historical background of probability theory, this thoroughly revised text examines all important aspects of mathematical probability - including random variables, probability distributions, characteristic and generating functions, stochatic convergence, and limit theorems - and provides an introduction to various types of statistical problems, covering the broad range of statistical inference.;Requiring a prerequisite in calculus for complete understanding of the topics discussed, the Second Edition contains new material on: univariate distributions; multivariate distributions; large-sample methods; decision theory; and applications of ANOVA.;A primary text for a year-long undergraduate course in statistics (but easily adapted for a one-semester course in probability only), Introduction to Probability and Statistics is for undergraduate students in a wide range of disciplines-statistics, probability, mathematics, social science, economics, engineering, agriculture, biometry, and education.
Statistical Process Monitoring and Optimization
Demonstrates ways to track industrial processes and performance, integrating related areas such as engineering process control, statistical reasoning in TQM, robust parameter design, control charts, multivariate process monitoring, capability indices, experimental design, empirical model building, and process optimization. The book covers a range of statistical methods and emphasizes practical applications of quality control systems in manufacturing, organization and planning.
Parameter Estimation in Reliability and Life Span Models
Offers an applications-oriented treatment of parameter estimation from both complete and censored samples; contains notations, simplified formats for estimates, graphical techniques, and numerous tables and charts allowing users to calculate estimates and analyze sample data quickly and easily. Furnishing numerous practical examples, this resource serves as a handy reference for statisticians, biometricians, medical researchers, operations research and quality control practitioners, reliability and design engineers, and all others involved in the analysis of sample data from skewed distributions, as well as a text for senior undergraduate and graduate students in statistics, quality control, operations research, mathematics and biometry courses.
Multivariate Analysis, Design of Experiments, and Survey Sampling
"Describes recent developments and surveys important topics in the areas of multivariate analysis, design of experiments, and survey sampling. Features the work of nearly 50 international leaders."
Handbook of Stochastic Analysis and Applications
An introduction to general theories of stochastic processes and modern martingale theory. The volume focuses on consistency, stability and contractivity under geometric invariance in numerical analysis, and discusses problems related to implementation, simulation, variable step size algorithms, and random number generation.
