This practical, user-oriented second edition describes how to use statistical modeling and analysis methods for forecasting and prediction problems. Statistical and mathematical terms are introduced only as they are needed, and every effort has been made to keep the mathematical and statistical prerequisites to a minimum. Every technique that is introduced is illustrated by fully worked numerical examples. Not only is the coverage of traditional forecasting methods greatly expanded in this new edition, but a number of new techniques and methods are covered as well.

Forecasting and time series analysis

Science & Math

Montgomery, Douglas C.

Johnson, Lynwood Albert

Mathematics

McGraw-Hill/Higher Education

Forecasting and Time Series Analysis

Johnson, Lynwood A.

Gardiner, John S.

McGraw=Hill

Applied Statistics and Probability for Engineers

Montgomery and Runger's bestselling engineering statistics text provides a practical approach oriented to engineering as well as chemical and physical sciences. By providing unique problem sets that reflect realistic situations, students learn how the material will be relevant in their careers. With a focus on how statistical tools are integrated into the engineering problem-solving process, all major aspects of engineering statistics are covered. Developed with sponsorship from the National Science Foundation, this text incorporates many insights from the authors' teaching experience along with feedback from numerous adopters of previous editions.

Runger, George C.

wiley

"This best-selling engineering statistics text provides a practical approach that is more oriented to engineering and the chemical and physical sciences than many similar texts. It is packed with unique problem sets that reflect realistic situations engineers will encounter in their working lives. This text shows how statistics, the science of data is just as important for engineers as the mechanical, electrical, and materials sciences"--

Applied Statistics and Probability for Engineers, 4th Edition, and JustAsk! Set

Book by Montgomery, Douglas C., Runger, George C.

JustAsk! Registration Card for Applied Statistics and Probability for Engineers

With Montgomery and Runger's best-selling engineering statistics text, you can learn how to apply statistics to real engineering situations. The text shows you how to use statistical methods to design and develop new products, and new manufacturing systems and processes. You'll gain a better understanding of how these methods are used in everyday work, and get a taste of practical engineering experience through real-world, engineering-based examples and exercises. Now revised, this Fourth Edition of Applied Statistics and Probability for Engineers features many new homework exercises, including a greater variation of problems and more computer problems.

Applied Statistics and Probability for Engineers, Student Solutions Manual

This Student Solutions Manual is meant to accompany Engineering Statistics, 4th Edition by Douglas Montgomery, which focuses on how statistical tools are integrated into the engineering problem-solving process, this book provides modern coverage of engineering statistics. It presents a wide range of techniques and methods that engineers will find useful in professional practice. All major aspects of engineering statistics are covered, including descriptive statistics, probability and probability distributions, building regression models, designing and analyzing engineering experiments, and more.

Engineering Statistics, Student Solutions Manual

Hubele, Norma F.

A comprehensive and up-to-date introduction to the fundamentals of regression analysis The Fourth Edition of Introduction to Linear Regression Analysis describes both the conventional and less common uses of linear regression in the practical context of today's mathematical and scientific research. This popular book blends both theory and application to equip the reader with an understanding of the basic principles necessary to apply regression model-building techniques in a wide variety of application environments. It assumes a working knowledge of basic statistics and a familiarity with hypothesis testing and confidence intervals, as well as the normal, t, x2, and F distributions. Illustrating all of the major procedures employed by the contemporary software packages MINITAB(r), SAS(r), and S-PLUS(r), the Fourth Edition begins with 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 discusses how transformations and weighted least squares can be used to resolve problems of model inadequacy and also how to deal with influential observations. Subsequent chapters discuss: * Indicator variables and the connection between regression and analysis-of-variance models * Variable selection and model-building techniques and strategies * The multicollinearity problem--its sources, effects, diagnostics, and remedial measures * Robust regression techniques such as M-estimators, and properties of robust estimators * The basics of nonlinear regression * Generalized linear models * Using SAS(r) for regression problems This book is a robust resource that offers solid methodology for statistical practitioners and professionals in the fields of engineering, physical and chemical sciences, economics, management, life and biological sciences, and the social sciences. Both the accompanying FTP site, which contains data sets, extensive problem solutions, software hints, and PowerPoint(r) slides, as well as the book's revised presentation of topics in increasing order of complexity, facilitate its use in a classroom setting. With its new exercises and structure, this book is highly recommended for upper-undergraduate and beginning graduate students in mathematics, engineering, and natural sciences. Scientists and engineers will find the book to be an excellent choice for reference and self-study.

Introduction to Linear Regression Analysis, 4th edition Student Solutions Manual (Wiley Series in Probability and Statistics)

Peck, Elizabeth A.

Vining, G. Geoffrey

Wiley-Interscience

This bestselling professional reference has helped over 100,000 engineers and scientists with the success of their experiments. The new edition includes more software examples taken from the three most dominant programs in the field: Minitab, JMP, and SAS. Additional material has also been added in several chapters, including new developments in robust design and factorial designs. New examples and exercises are also presented to illustrate the use of designed experiments in service and transactional organizations. Engineers will be able to apply this information to improve the quality and efficiency of working systems.

Design and Analysis of Experiments

Computers & Technology

Computer Science

Applied Statistics and Probability for Engineers 4th Edition with Wiley Plus WebCT Powerpack Set

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Books by Montgomery, Douglas C.