Statistics for Engineering and the Sciences (4th Edition). Este artículo no está disponible.Statistics for Engineering and the Sciences (4th Edition)

This book illustrates basic statistical concepts with extensive applications in engineering and scientific contexts. The book includes optional theoretical exercises, allowing readers who choose to emphasize theory to do so with requiring additional materials. The fourth edition contains SAS and MINITAB computer printout results for all analyses performed?plus new exercises based on magazine and journal articles and news reports. KEY TOPICS: A section on "Detecting Normal Distributions" (Chapter 5) gives readers insights on when it is reasonable to assume that underlying data is normally distributed. There is a comprehensive example on model building (Chapter 13) and emphasis on the regression approach to a Nova (also presents the traditional approach). There are two sections discussing principles of experimental design, i.e., noise-reducing and volume-increasing design, a section on "Total Quality Management" and coverage of statistical computing. There are optional, calculus-based theoretical exercises, and real data sets, extracted from scientific studies, are provided in an appendix. Numerical answers to all applied exercises are included in an appendix?giving readers immediate feedback on their work.

This book illustrates basic statistical concepts with extensive applications in engineering and scientific contexts. The book includes optional theoretical exercises, allowing readers who choose to emphasize theory to do so with requiring additional materials. The fourth edition contains SAS and MINITAB computer printout results for all analyses performed?plus new exercises based on magazine and journal articles and news reports. KEY TOPICS: A section on "Detecting Normal Distributions" (Chapter 5) gives readers insights on when it is reasonable to assume that underlying data is normally distributed. There is a comprehensive example on model building (Chapter 13) and emphasis on the regression approach to a Nova (also presents the traditional approach). There are two sections discussing principles of experimental design, i.e., noise-reducing and volume-increasing design, a section on "Total Quality Management" and coverage of statistical computing. There are optional, calculus-based theoretical exercises, and real data sets, extracted from scientific studies, are provided in an appendix. Numerical answers to all applied exercises are included in an appendix?giving readers immediate feedback on their work.