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Design and Analysis of Experiments provides a rigorous introduction to product and process design improvement through quality and performance optimization. Clear demonstration of widely practiced techniques and procedures allows readers to master fundamental concepts, develop design and analysis skills, and use experimental models and results in real-world applications. Detailed coverage of factorial and fractional factorial design, response s...

This book presents an organized approach to quality management, control, and improvement. Because quality problems usually are the outcome of uncontrolled or excessive variability, statistical tools and other analytical methods play an important role in solving these problems. However, these techniques need to be implemented within a management structure that will ensure success. This text focuses on both the management structure and the stati...

As the Solutions Manual, this book is meant to accompany the main title, Introduction to Linear Regression Analysis, Sixth Edition. Clearly balancing theory with applications, this book describes both the conventional and less common uses of linear regression in the practical context of today's mathematical and scientific research. Beginning with a general introduction to regression modeling, including typical applications, the book then outli...

In statistics, linear regression is a linear approach to modelling the relationship between a scalar response and one or more explanatory variables. A linear regression model attempts to explain the relationship between two or more variables using a straight line."--

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Once solely the domain of engineers, quality control has become a vital business operation used to increase productivity and secure competitive advantage. Introduction to Statistical Quality Control offers a detailed presentation of the modern statistical methods for quality control and improvement. Thorough coverage of statistical process control (SPC) demonstrates the efficacy of statistically-oriented experiments in the context of process c...

Applied Statistics and Probability for Engineers provides a practical approach to probability and statistical methods. Students learn how the material will be relevant in their careers by including a rich collection of examples and problem sets that reflect realistic applications and situations. This product focuses on real engineering applications and real engineering solutions while including material on the bootstrap, increased emphasis on ...

A comprehensive and up-to-date introduction to the fundamentals of regression analysis This set includes Introduction to Linear Regression Analysis, Sixth Edition and the Solutions Manual to accompany the text. This book 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 basi...

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Montgomery, Runger, and Hubele provide modern coverage of engineering statistics, focusing on how statistical tools are integrated into the engineering problem-solving process. All major aspects of engineering statistics are covered, including descriptive statistics, probability and probability distributions, statistical test and confidence intervals for one and two samples, building regression models, designing and analyzing engineering exper...

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This Fifth Edition introduces and features the use of R and JMP software. SAS, S-Plus, and Minitabcontinue to be employed in this new edition, and the output from all of these packages can be found throughout the book.

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Real Engineering Situations, Real Engineering Data 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.

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