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Statistics

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Miller & Freund's Probability and Statistics for Engineers, 7/E
Richard Johnson
Irwin Miller
John Freund

ISBN-10: 0131437453
ISBN-13: 9780131437456

Publisher: Prentice Hall
Copyright: 2005
Format: Cloth; 656 pp
Published: 08/17/2004

Suggested retail price: $137.33
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For an introductory, one or two semester, sophomore-junior level course in Probability and Statistics or Applied Statistics for engineering, physical science, and mathematics students.

This example- and exercise-rich exploration of both elementary probability and basic statistics emphasizes engineering and science applications—many using data collected from the author's consulting experience. In later chapters, the text emphasizes designed experiments, especially two-level factorial design.

  • Case studies in the first two chapters.

    • These applications illustrate the power of even simple statistical methods to suggest changes that make major improvements in production processes.

  • Expanded Chapter 1—Includes material on the distinction between sample and population, good and bad samples, and the use of a random number table to choose samples.

    • Exposes students to important, basic issues early.

  • Improved standard normal distribution material—The normal table includes both negative and positive z values. Further, graphs of the normal density are used to guide students in evaluating normal probabilities.

    • Saves the student manipulations when evaluating normal probability.

  • Graphs of the sampling distribution showing the critical region and P value accompany the examples of testing hypotheses.

    • These graphs help reinforce student understanding of the critical region, significance level, and P value.

  • Summary tables of testing procedures.

    • Makes for easier summary reference for students.

  • Coverage of curve fitting—Enhanced introduction to fitting a straight line by least squares. The role of the correlation coefficient and its own properties are highlighted.

    • What was previously a cumbersome presentation is now much more streamlined providing for greater clarification.

  • Section on graphic presentation of 22 and 23 designs—Includes coverage of blocking.

    • Serves as a stand-alone introduction to the design of experiments for those instructors who can only devote two or three lectures to the subject.

  • Clear, concise presentation.
  • Vast, rich collection of problem sets.
  • Solid treatment of confidence interval techniques and hypothesis testing procedures.

    • Clearly and consistently delineates for students the steps for hypothesis testing in each application.

  • Clear, current coverage of two-level factorial design.

    • To explore interactions, engineers have to know about experiments where more than one variable has been changed at the same time in design.

  • Full chapter on modern ideas of quality improvement. Provides up-to-date coverage of this popular significant trend in the field.
  • Accessible discussion on joint distributions and the properties of expectation.

    • This is a difficult topic not always covered in the course, but if so desired, here is a nice, quick treatment of it.

  • NEW - Do's and Don'ts at the end of each chapter help students to apply statistics correctly to avoid misuses.
  • NEW - Updated computer exercises for MINITAB.
  • NEW - Several new data sets have been added—Drawn from both author Johnson's own consulting activities and discussions with scientists and engineers about their statistical problems.

    • Help to illustrate the statistical methods and reasoning required in order to draw generalizations from data collected in actual experiments.

  • Do's and Don'ts at the end of each chapter help students to apply statistics correctly to avoid misuses.
  • Updated computer exercises for MINITAB.
  • Several new data sets have been added—Drawn from both author Johnson's own consulting activities and discussions with scientists and engineers about their statistical problems.

    • Help to illustrate the statistical methods and reasoning required in order to draw generalizations from data collected in actual experiments.



 1. Introduction.


 2. Treatment of Data.


 3. Probability.


 4. Probability Distributions.


 5. Probability Densities.


 6. Sampling Distribution.


 7. Inferences Concerning Means.


 8. Inferences Concerning Variances.


 9. Inferences Concerning Proportions.


10. Nonparametric Tests.


11. Curve Fitting.


12. Analysis of Variance.


13. Factorial Experimentation.


14. The Statistical Content of Quality—Improvement Programs.


15. Applications to Reliability and Life Testing.


Bibliography.


Statistical Tables.


Answers to Odd-Numbered Exercises.


Index.

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