Practical Engineering Statistics
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English
PRACTICAL ENGINEERING STATISTICS
This lucidly written book offers engineers and advanced studentsall the essential statistical methods and techniques used inday-to-day engineering work. Without unnecessary digressions intoformal proofs or derivations, Practical Engineering Statisticsshows how to select the appropriate statistical method for aspecific task and then how to apply it correctly and confidently.Clear explanations supported by real-world examples lead the readerstep-by-step through each procedure. Topics covered include productdesign and development; estimations of the mean value andvariability of measured data; comparison of processes or products;the relationships between variables; and more.
With its emphasis on practical use and its full range ofengineering applications, Practical Engineering Statistics servesas an indispensable, time-saving reference for all engineersworking in design, reliability, assurance, scheduling, andmanufacturing.
PRACTICAL ENGINEERING STATISTICS
While engineers are frequently involved in projects that requirethe application of statistical methods to analysis, prediction, andplanning, their background in statistics is often insufficient tothe task. In many cases the engineer has had little training instatistics beyond the concepts of the mean, the standard deviation,the median, and the quartile. Even those who have had one or morecourses in statistics will, at times, encounter problems which arebeyond their capacity to solve or understand.
Practical Engineering Statistics is designed to give engineers theknowledge to select the statistical approach that is mostappropriate to the problem at hand and the skills to confidentlyapply this approach to specific cases. It provides the engineerwith the statistical tools needed to perform the job effectively,whether it is pro-duct design and development, estimation of themean value and variability of measured data, comparison ofprocesses or products, or the relationship between variables.
Its authors bring two different areas of expertise to this uniquebook: statistics and engineering physics. In Practical EngineeringStatistics their collaboration has produced a book that clearlyleads engineers step-by-step through each procedure, withouttime-consuming and unnecessary discussions of proofs andderivations. Statistical procedures are discussed and explained indetail and demonstrated through real-world sample problems, withcorrect answers always provided. Readers learn how to determinewhich data represent true observations and which, through humanerror or flawed data, are false observations.
Complex problems are presented with computer printouts of thedatabase, intermediate steps, and results. Numerous illustrationsand tables of all commonly used distributions enhance theusefulness of this invaluable book.
Virtually all engineers and advanced students, especially those inmechanical, civil, electrical, aerospace, and chemical engineering,Practical Engineering Statistics is an indispensable reference thatwill give them the tools to do the statistical part of their workquickly and accurately.
This lucidly written book offers engineers and advanced studentsall the essential statistical methods and techniques used inday-to-day engineering work. Without unnecessary digressions intoformal proofs or derivations, Practical Engineering Statisticsshows how to select the appropriate statistical method for aspecific task and then how to apply it correctly and confidently.Clear explanations supported by real-world examples lead the readerstep-by-step through each procedure. Topics covered include productdesign and development; estimations of the mean value andvariability of measured data; comparison of processes or products;the relationships between variables; and more.
With its emphasis on practical use and its full range ofengineering applications, Practical Engineering Statistics servesas an indispensable, time-saving reference for all engineersworking in design, reliability, assurance, scheduling, andmanufacturing.
PRACTICAL ENGINEERING STATISTICS
While engineers are frequently involved in projects that requirethe application of statistical methods to analysis, prediction, andplanning, their background in statistics is often insufficient tothe task. In many cases the engineer has had little training instatistics beyond the concepts of the mean, the standard deviation,the median, and the quartile. Even those who have had one or morecourses in statistics will, at times, encounter problems which arebeyond their capacity to solve or understand.
Practical Engineering Statistics is designed to give engineers theknowledge to select the statistical approach that is mostappropriate to the problem at hand and the skills to confidentlyapply this approach to specific cases. It provides the engineerwith the statistical tools needed to perform the job effectively,whether it is pro-duct design and development, estimation of themean value and variability of measured data, comparison ofprocesses or products, or the relationship between variables.
Its authors bring two different areas of expertise to this uniquebook: statistics and engineering physics. In Practical EngineeringStatistics their collaboration has produced a book that clearlyleads engineers step-by-step through each procedure, withouttime-consuming and unnecessary discussions of proofs andderivations. Statistical procedures are discussed and explained indetail and demonstrated through real-world sample problems, withcorrect answers always provided. Readers learn how to determinewhich data represent true observations and which, through humanerror or flawed data, are false observations.
Complex problems are presented with computer printouts of thedatabase, intermediate steps, and results. Numerous illustrationsand tables of all commonly used distributions enhance theusefulness of this invaluable book.
Virtually all engineers and advanced students, especially those inmechanical, civil, electrical, aerospace, and chemical engineering,Practical Engineering Statistics is an indispensable reference thatwill give them the tools to do the statistical part of their workquickly and accurately.
English
DANIEL SCHIFF is a consulting engineer and was formerly ChiefScientist of Assurance Technology Corporation. Dr. Schiff receivedhis PhD in nuclear physics, holds six U.S. patents, and is aregistered professional engineer in Massachusetts. His current workincludes energy efficient design, statistical analysis, and shockand vibration analysis. He is the author of Dynamic Analysis andFailure Modes of Simple Structures, also published by Wiley.
RALPH B. D'AGOSTINO is Professor of Mathematics, Statistics, PublicHealth and Law at Boston University, and formerly Chairman of theMathematics Department. In addition, Dr. D'Agostino is Director ofthe University's Statistics and Consulting Unit. He is an activeresearcher and consultant to both government and industry, a Fellowof the American Statistical Association and recipient of theMetcalf Cup and Prize for Excellence in Teaching at BostonUniversity. He is coauthor of Factor Analysis: An Applied Approach(with E. E. Coreton) and Goodness-of-Fit Techniques (with M. A.Stephens).
RALPH B. D'AGOSTINO is Professor of Mathematics, Statistics, PublicHealth and Law at Boston University, and formerly Chairman of theMathematics Department. In addition, Dr. D'Agostino is Director ofthe University's Statistics and Consulting Unit. He is an activeresearcher and consultant to both government and industry, a Fellowof the American Statistical Association and recipient of theMetcalf Cup and Prize for Excellence in Teaching at BostonUniversity. He is coauthor of Factor Analysis: An Applied Approach(with E. E. Coreton) and Goodness-of-Fit Techniques (with M. A.Stephens).
English
Statistical Inference.
Probability Models.
Descriptive Statistics.
Inferential Statistics: Mean Values.
Analysis of Proportions and Categorical Data.
Variability.
Analysis of Variance and Experimental Design I. Outliers.
Extreme Value Analysis.
Sensitivity Testing.
Regression and Correlation.
Experimental Design II.
Control Charts.
Reliability and Lifetime.
Appendix.
Bibliography.
Index.
Probability Models.
Descriptive Statistics.
Inferential Statistics: Mean Values.
Analysis of Proportions and Categorical Data.
Variability.
Analysis of Variance and Experimental Design I. Outliers.
Extreme Value Analysis.
Sensitivity Testing.
Regression and Correlation.
Experimental Design II.
Control Charts.
Reliability and Lifetime.
Appendix.
Bibliography.
Index.
