Statistics

This product accompanies:
Mendenhall & Sincich,  Statistics for Engineering and the Sciences, 5/E

• many new applied exercises are based on information from recent engineering and scientific journals, magazine articles, and news reports; all information is referenced.

• a section on “Detecting Normal Distributions”(Chapter 5) gives students insights on when it is reasonable to assume that underlying data is normally distributed.

• a comprehensive example on model building (Chapter 13).

• emphasis on the regression approach to a Nova (also presents the traditional approach).

• two sections discussing principles of experimental design—ie., noise-reducing and volume-increasing design (Chapter 14).

• section on Total Quality Management (Chapter 16).

• includes coverage of statistical computing.

  • computer applications include clear, easy-to-follow instructions on how to use statistical software (SAS and MINITAB).

  • whenever an analysis is performed for a case study or example, a computer printout of the results is included—enabling students to focus on the interpretation of results and the proper application of methods.

  • Computer Lab sections following most chapters give students tutorials in SAS and MINITAB; each lab lists the commands used to generate the printouts displayed in the chapter and gives a brief explanation of each command.

  • menu-driven, user-friendly ASP statistical software included with the text performs all necessary computations—allowing students to concentrate on interpretations.

• optional, calculus-based, theoretical exercises are included, for courses emphasizing theory.

• real data sets, extracted from scientific studies, are provided in an appendix—allowing instructors to motivate and explain basic statistical concepts with real scientific data.

• numerical answers to all applied exercises are included in an appendix—giving students immediate feedback on their work.

 1. Introduction.


 2. Descriptive Statistics.


 3. Probability.


 4. Discrete Random Variables.


 5. Continuous Random Variables.


 6. Bivariate Probability Distributions.


 7. Sampling Distributions.


 8. Estimation.


 9. Tests of Hypothesis.


10. Categorical Data.


11. Simple Linear Regression Analysis.


12. Multiple Regression Analysis.


13. Model Building.


14. Analysis of Variants for designed experiments.


15. Nonparametric Statistics.


16. Statistical Process and Quality Control.


17. Product and System Reliability.


Appendix I. Matrix Algebra.


Appendix II. Useful Statistical Tables.


Appendix III. DDT Analysis on Fish Samples, Tennessee River, Alabama.


Appendix IV. Central Processing Unit(CPU) Times of 1,000 Computer Jobs.


Appendix V. Percentage Iron Content for 390 Iron Ore Specimens.


Appendix VI. ASP Tutorial.


Answers to Selected Exercises.


Index.

Probability & Statistics - Engineers & Scientists  (Statistics)

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  Statistics for Engineering and the Sciences, 5/E
  Mendenhall & Sincich
  ©2007 | Pearson | Paper; 1072 pp | Instock
  ISBN-10: 0131877062 | ISBN-13: 9780131877061
  Suggested retail price: $73.33  Buy from myPearsonStoreNet price: $55.00  (What's this?)Brief Description

  

  For engineering statistics courses in departments of Statistics and Engineering.

   

  This text is designed for a two-semester introductory course in statistics for students majoring in engineering or any of the 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.

  
  

  Datasets and other resources (where applicable) for this book are available here.

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