This text is designed for a two-semester introductory course in statistics for students majoring in engineering or any of hte physical sciences. Inevitalby, once these studenrts graduate and are employed, they will be involved in the collection and analysis of data and will be required to think critically about the results. Consequently, they need to acquire knowledge of the basi

c concepts of data description and statistical inference and familiarity with statistical methods they are required to use on the job.The text includes optional theoretical exercises allowing instructors who choose to emphasize theory to do so without requiring additional materials.

The assumed mathematical background is a two-semester sequence in calculus - that is, the course could be taught to students of average mathematical talent and with a basic understanding of the principles of differential and integral calculus.

**Features**

...show moreThe assumed mathematical background is a two-semester sequence in calculus - that is, the course could be taught to students of average mathematical talent and with a basic understanding of the principles of differential and integral calculus.

- 1. Blend of theory and applications. The basic theoretical concepts of mathematical statistics are integrated with a two-semester presentation of statistical methodology. Thus, the instructor has the option of presenting a course with either of two characteristics -- a course stressing basic concepts and applied statistics or a course that, while still tilted toward application, presents a modes introduction to the theory underlying statistical inference.
- 2. Statistical software applications with tutorials. The instructor and student have the option of using statistical software to perform the statistical calculations. Printouts from three popular statistical software packages -- SAS, SPSS, and Minitab -- as well as Microsoft Excel output are fully integrated into text. Tutorials with menu screens and dialog boxes are provided in Appendices C, D, and E. These tutorials are designed for the novice user; no prior experience with the software is needed.
- 3. Blended coverage of topics and applications. To meet the diverse needs of future engineers and scientists, the text provides coverage of a wide range of data analysis topics.The material on multiple regression and model building (Chapters 11-12), principles of experimental design (Chapter 13), quality control (Chapter 16), and reliability (Chapter 17) sets the text apart from the typical introductory statistics text. Although the material often refers to theoretical concepts, the presentation is oriented toward applications.
- 4. Numerous real data-based exercises.The text contains a large number of applied exercises designed to motivate a student and suggest future uses of the methodology. Nearly every exercise is based on data or experimental results extracted from professional journals or obtained from organizations in the engineering and physical sciences. Exercises are located at the ends of key sections and at the ends of chapters.
- 5. ''Statistics in Action'' case studies.The 5th edition of the text now includes a contemporary scientific study (''Statistics in Action'') and the accompanying data and analysis at the end of each chapter. Our goal is to show students the importance of applying sound statistical techniques in order to evaluate the findings and to think through the statistical issues involved.
- 6. Data sets provided on CD.All of the data sets associated with examples, exercises, and cases are provided on a CD that accompanies this text. (Each data set is marked with a CD icon and file name in the text.) The data files are saved in four different formats: MINITAB, SAS, SPSS, and ASCII (for easy importing into other statistical software packages). By analyzing these data using statistical software, calculations are minimized, allowing the student to concentrate on the interpretation of the results.
- 7. Numerical answers to exercises available at the back of the book. This gives students the guidence and immediate feedback they require as they work the exercises.

This text is designed for a two-semester introductory course in statistics for students majoring in engineering or any of hte physical sciences. Inevitalby, once these studenrts graduate and are employed, they will be involved in the collection and analysis of data and will be required to think critically about the results. Consequently, they need to acquire knowledge of the basic concepts of data description and statistical inference and familiarity with statistical methods they are required to use on the job.The text includes optional theoretical exercises allowing instructors who choose to emphasize theory to do so without requiring additional materials.

The assumed mathematical background is a two-semester sequence in calculus - that is, the course could be taught to students of average mathematical talent and with a basic understanding of the principles of differential and integral calculus.

- 1. Blend of theory and applications. The basic theoretical concepts of mathematical statistics are integrated with a two-semester presentation of statistical methodology. Thus, the instructor has the option of presenting a course with either of two characteristics -- a course stressing basic concepts and applied statistics or a course that, while still tilted toward application, presents a modes introduction to the theory underlying statistical inference.
- 2. Statistical software applications with tutorials. The instructor and student have the option of using statistical software to perform the statistical calculations. Printouts from three popular statistical software packages -- SAS, SPSS, and Minitab -- as well as Microsoft Excel output are fully integrated into text. Tutorials with menu screens and dialog boxes are provided in Appendices C, D, and E. These tutorials are designed for the novice user; no prior experience with the software is needed.
- 3. Blended coverage of topics and applications. To meet the diverse needs of future engineers and scientists, the text provides coverage of a wide range of data analysis topics.The material on multiple regression and model building (Chapters 11-12), principles of experimental design (Chapter 13), quality control (Chapter 16), and reliability (Chapter 17) sets the text apart from the typical introductory statistics text. Although the material often refers to theoretical concepts, the presentation is oriented toward applications.
- 4. Numerous real data-based exercises.The text contains a large number of applied exercises designed to motivate a student and suggest future uses of the methodology. Nearly every exercise is based on data or experimental results extracted from professional journals or obtained from organizations in the engineering and physical sciences. Exercises are located at the ends of key sections and at the ends of chapters.
- 5. ''Statistics in Action'' case studies.The 5th edition of the text now includes a contemporary scientific study (''Statistics in Action'') and the accompanying data and analysis at the end of each chapter. Our goal is to show students the importance of applying sound statistical techniques in order to evaluate the findings and to think through the statistical issues involved.
- 6. Data sets provided on CD.All of the data sets associated with examples, exercises, and cases are provided on a CD that accompanies this text. (Each data set is marked with a CD icon and file name in the text.) The data files are saved in four different formats: MINITAB, SAS, SPSS, and ASCII (for easy importing into other statistical software packages). By analyzing these data using statistical software, calculations are minimized, allowing the student to concentrate on the interpretation of the results.
- 7. Numerical answers to exercises available at the back of the book. This gives students the guidence and immediate feedback they require as they work the exercises.

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