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Integrates the statistical computing package MINITAB(tm) into an Introductory Statistics course, using Statistics by McClave/Sincich, 9/e.
The Handbook provides a detailed evaluation of what can realistically be achieved by remote sensing in an operational coastal management context. It takes the user through the planning and implementation of remote sensing projects from the setting of realistic objectives, deciding which imagery will be most appropriate to achieve those objectives, the acquisition, geometric and radiometric correction of imagery, the field survey methods needed to ground-truth the imagery and guide image classification, the image processing techniques required to optimise outputs, through the image interpretation and evaluation of the accuracy of outputs. Linked to the Handbook is a computer-based remote sensing distance-learning module: Applications of satellite and airborne image data to coastal management available free of charge via www.unesco.bilko.org
Other volumes in the Wiley Series in Probability and MathematicalStatistics, Ralph A. Bradley, J. Stuart Hunter, David G. Kendall,& Geoffrey S. Watson, Advisory Editors Statistical Models inApplied Science Karl V. Bury Of direct interest to engineers andapplied scientists, this book presents general principles ofstatistics and specific distribution methods and models. Prominentdistribution properties and methods that are useful over a widerange of applications are covered in detail. The strengths andweaknesses of the distributional models are fully described, givingthe reader a firm, intuitive approach to the selection of the modelmost appropriate to the problem at hand. 1975 656 pp. FittingEquations To Data Computer Analysis of Multifactor Data forScientists and Engineers Cuthbert Daniel & Fred S. Wood Withthe assistance of John W. Gorman The purpose of this book is tohelp the serious data analyst, scientist, or engineer with acomputer to: recognize the strengths and limitations of his data;test the assumptions implicit in the least squares methods used tofit the data; select appropriate forms of the variables; judgewhich combinations of variables are most influential; and state theconditions under which the fitted equations are applicable.Throughout, mathematics is kept at the level of college algebra.1971 342 pp. Methods for Statistical Analysis of Reliability AndLife Data Nancy R. Mann, Ray E. Schafer & Nozer D. SingpurwallaThis book introduces failure models commonly used in reliabilityanalysis, and presents the most useful methods for analyzing thelife data of these models. Highlights include: material onaccelerated life testing; a comprehensive treatment of estimationand hypothesis testing; a critical survey of methods forsystem-reliability confidence bonds; and methods for simulation oflife data and for testing fit. 1974 564 pp.
Zentrifugalpumpen werden in den verschiedensten Bereichen eingesetzt - etwa in städtischen Versorgungssystemen zum Pumpen von Wasser oder in Maschinen zum Pumpen von Öl -, denn sie sind zuverlässig und dabei moderat im Kosten- und Wartungsaufwand. Der Autor dieses Buches kann auf Erfahrungen aus langjähriger Tätigkeit in der Industrie zurückgreifen. Er erklärt Ihnen Konstruktion und Analyse der wichtigsten Pumpensysteme. (11/00)
The extraordinary breakthrough management program--heralded by GE, Motorola, and AlliedSignal--that is sweeping corporate America with its unprecedented ability to achieve superior financial results. Six Sigma is the most powerful breakthrough management tool ever devised, promising increased market share, cost reductions, and dramatic improvements in bottom-line profitability for companies of any size. The darling of Wall Street, it has become the mantra of Fortune 500 boardrooms around the world because it works. What is Six Sigma? It is first and foremost a business process that enables companies to increase profits dramatically by streamlining operations, improving quality, and eliminating defects or mistakes in everything a company does, from filling out purchase orders to manufacturing airplane engines. While traditional quality programs have focused on detecting and correcting defects, Six Sigma encompasses something broader: It provides specific methods to re-create the process itself so that defects are never produced in the first place. Most companies operate at a three- to four-sigma level, where the cost of defects is roughly 20 to 30 percent of revenues. By approaching Six Sigma--fewer than one defect per 3.4 million opportunities--the cost of quality drops to less than 1 percent of sales. This is because the highest quality also results in the lowest costs. When GE reduced its costs from 20 percent to less than 10 percent, it saved a billion dollars in just two years--money that goes directly to the bottom line. This is the reason Wall Street and corporations as diverse as Sony, Ford, Nokia, Texas Instruments, Canon, Hitachi, Lockheed Martin, American Express, Toshiba, DuPont, and Polaroid have embarked on corporate-wide Six Sigma programs. Six Sigma should be of paramount importance to every forward-thinking executive and manager determined to make their company world-class in their industry.
A comprehensive reference handbook on the important aspects of trace elements in the land environment. Each chapter addresses a particular element and gives a general introduction to their role in the environment, where they come from, and their biogeochemical cycles. In addition to a complete updating of each of the element chapters, this new edition has new chapters devoted to aluminum and iron, soil contamination, remediation and trace elements in aquatic ecosystems. In short, an essential resource for environmental scientists and chemists, regulators and policy makers.
Praise for the Fourth Edition "As with previous editions, the authors have produced a leading textbook on regression." —Journal of the American Statistical Association A comprehensive and up-to-date introduction to the fundamentals of regression analysis Introduction to Linear Regression Analysis, Fifth Edition continues to present both the conventional and less common uses of linear regression in today’s cutting-edge scientific research. The authors blend both theory and application to equip readers with an understanding of the basic principles needed to apply regression model-building techniques in various fields of study, including engineering, management, and the health sciences. Following a general introduction to regression modeling, including typical applications, a host of technical tools are outlined such as basic inference procedures, introductory aspects of model adequacy checking, and polynomial regression models and their variations. The book then discusses how transformations and weighted least squares can be used to resolve problems of model inadequacy and also how to deal with influential observations. The Fifth Edition features numerous newly added topics, including: A chapter on regression analysis of time series data that presents the Durbin-Watson test and other techniques for detecting autocorrelation as well as parameter estimation in time series regression models Regression models with random effects in addition to a discussion on subsampling and the importance of the mixed model Tests on individual regression coefficients and subsets of coefficients Examples of current uses of simple linear regression models and the use of multiple regression models for understanding patient satisfaction data. In addition to Minitab, SAS, and S-PLUS, the authors have incorporated JMP and the freely available R software to illustrate the discussed techniques and procedures in this new edition. Numerous exercises have been added throughout, allowing readers to test their understanding of the material. Introduction to Linear Regression Analysis, Fifth Edition is an excellent book for statistics and engineering courses on regression at the upper-undergraduate and graduate levels. The book also serves as a valuable, robust resource for professionals in the fields of engineering, life and biological sciences, and the social sciences.
This book reveals the development of students' understanding of statistical literacy. It provides a way to "see" student thinking and gives readers a deeper sense of how students think about important statistical topics. Intended as a complement to curriculum documents and textbook series, it is consistent with the current principles and standards of the National Council of Teachers of Mathematics. The term "statistical literacy" is used to emphasize that the purpose of the school curriculum should not be to turn out statisticians but to prepare statistically literate school graduates who are prepared to participate in social decision making. Based on ten years of research--with reference to other significant research as appropriate--the book looks at students' thinking in relation to tasks based on sampling, graphical representations, averages, chance, beginning inference, and variation, which are essential to later work in formal statistics. For those students who do not proceed to formal study, as well as those who do, these concepts provide a basis for decision making or questioning when presented with claims based on data in societal settings. Statistical Literacy at School: Growth and Goals: *establishes an overall framework for statistical literacy in terms of both the links to specific school curricula and the wider appreciation of contexts within which chance and data-handling ideas are applied; *demonstrates, within this framework, that there are many connections among specific ideas and constructs; *provides tasks, adaptable for classroom or assessment use, that are appropriate for the goals of statistical literacy; *presents extensive examples of student performance on the tasks, illustrating hierarchies of achievement, to assist in monitoring gains and meeting the goals of statistical literacy; and *includes a summary of analysis of survey data that suggests a developmental hierarchy for students over the years of schooling with respect to the goal of statistical literacy. Statistical Literacy at School: Growth and Goals is directed to researchers, curriculum developers, professionals, and students in mathematics education as well those across the curriculum who are interested in students' cognitive development within the field; to teachers who want to focus on the concepts involved in statistical literacy without the use of formal statistical techniques; and to statisticians who are interested in the development of student understanding before students are exposed to the formal study of statistics.
Offering deep insight into the connections between design choice and the resulting statistical analysis, Design of Experiments: An Introduction Based on Linear Models explores how experiments are designed using the language of linear statistical models. The book presents an organized framework for understanding the statistical aspects of experiment
The Guide to Minitab includes both a Getting Started with Minitab section and hands-on, self-paced Tutorials designed to teach students how to use the software capabilities through a variety of approaches. The Tutorials cover all of the primary features and capabilities of MINITAB, including graphical and numerical methods for one and two or more variables, bivariate analysis, total quality management tools, time series analysis, and taking data from the web, to name a few. MINITAB is an easy-to-use general-purpose statistical computing package for analyzing data. It is a flexible and powerful tool that was designed from the beginning to be used by students and researchers new to statistics. It is now one of the most widely used statistics packages in the world. Minitab performs horribly tedious computations and produces accurate and professional quality graphs almost instantly. This power frees the user to focus on the exploration of the structure of the data and the interpretation of the output. MINITAB software not included.