Professional

Applied Statistics for Engineers and Scientists, 3rd Edition

  • Jay L. Devore California Polytechnic State University, San Luis Obispo
  • Nicholas R. Farnum California State University, Fullerton
  • Jimmy A. Doi California Polytechnic State University, San Luis Obispo
  • ISBN-10: 113311136X  |  ISBN-13: 9781133111368
  • 656 Pages
  • Previous Editions: 2005
  • © 2014 | Published
  • List Price = $ 187.95
  • For quantity discounts, Contact your Representative
  • For single copy purchases, visit CengageBrain.com

About

Overview

This concise book for engineering and sciences students emphasizes modern statistical methodology and data analysis. APPLIED STATISTICS FOR ENGINEERS AND SCIENTISTS emphasizes application of methods to real problems, with real examples throughout. Available with InfoTrac® Student Collections http://gocengage.com/infotrac.

Features and Benefits

  • The integration of the "Six Sigma Terminology" in Chapter 6 adds to the text's modern approach.
  • Describe the key features (e.g. a chapter in the TOC, a feature to spotlight, a supplement to call out, and technology to mention) instructors will want to be aware of.
  • Examples that use real data from industry reports and articles introduce students to real-world situations while they learn statistical concepts.
  • The authors cover all the important topics concisely, giving students a solid understanding of both statistical methods and design with a problem-solving focus.
  • The authors emphasize modern statistical methods including quality and design of experiments to give students exposure to practical applications.
  • An emphasis on graphical data analysis methods is consistent with the authors' computer-integrated approach.
  • Practical computer pedagogy is integrated throughout the book so that learning of concepts can focus on real applications, using output from the most widely used statistical packages, such as MINITAB, JMP IN, SAS, and S-Plus.
  • Numerous relevant, current exercises and examples appear throughout.

Table of Contents

1. DATA AND DISTRIBUTIONS.
Populations, Samples and Processes. Visual Displays for Univariate Data. Describing Distributions. The Normal Distribution. Other Continuous Distributions. Several Useful Discrete Distributions. Supplementary Exercises. Bibliography.
2. NUMERICAL SUMMARY MEASURES.
Measures of Center. Measures of Variability. More Detailed Summary Quantities. Quantile Plots. Supplementary Exercises. Bibliography.
3. BIVARIATE AND MULTIVARIATE DATA AND DISTRIBUTIONS.
Scatter Plots. Correlation. Fitting a Line to Bivariate Data. Nonlinear Relationships. Using More Than One Predictor. Joint Distributions. Supplementary Exercises. Bibliography.
4. OBTAINING DATA.
Operational Definitions. Data from Sampling. Data from Experiments. Measurement Systems. Supplementary Exercises. Bibliography.
5. PROBABILITY AND SAMPLING DISTRIBUTIONS.
Chance Experiments. Probability Concepts. Conditional Probability and Independence. Random Variables. Sampling Distributions. Describing Sampling Distributions. Supplementary Exercises. Bibliography.
6. QUALITY CONTROL.
Terminology. How Control Charts Work. Control Charts for Mean and Variance. Process Capability Analysis. Control Charts for Attribute Data. Reliability. Supplementary Exercises. Bibliography.
7. ESTIMATION AND STATISTICAL INTERVALS.
Point Estimation. Large-Sample Confidence Intervals for a Population Mean. More Large-Sample Confidence Intervals. Small-Sample Intervals Based on a Normal Population Distribution. Intervals for µ1-µ2 Based on a Normal Population Distributions. Other Topics in Estimation (Optional). Supplementary Exercises. Bibliography.
8. TESTING STATISTICAL HYPOTHESES.
Hypotheses and Test Procedures. Tests Concerning Hypotheses About Means. Tests Concerning Hypotheses About a Categorical Population. Testing the Form of a Distribution. Further Aspects of Hypothesis Testing. Supplementary Exercises. Bibliography.
9. THE ANALYSIS OF VARIANCE.
Terminology and Concepts. Single-Factor ANOVA. Interpreting ANOVA Results. Randomized Block Experiments. Supplementary Exercises. Bibliography.
10. EXPERIMENTAL DESIGN.
Terminology and Concepts. Two-Factor Designs. Multifactor Designs. 2k Designs. Fractional Factorial Designs. Supplementary Exercises. Bibliography.
11. INFERENTIAL METHODS IN REGRESSION AND CORRELATION.
Regression and Models Involving a Single Independent Variable. Inferences About the Slope Coefficient ß. Inferences Based on the Estimated Regression Line. Multiple Regression Models. Inferences in Multiple Regression. Further Aspects of Regression Analysis. Supplementary Exercises. Bibliography.
APPENDIX TABLES.
ANSWERS TO ODD-NUMBERED EXERCISES.
INDEX.

What's New

  • New exercises and examples, based on real data and information from published sources, reinforce a practical, realistic approach that helps students relate to and understand statistical concepts better.
  • Computer output has been updated to reflect the latest technology.
  • InfoTrac® Student Collections are specialized databases expertly drawn from the Gale Academic One library. Each InfoTrac® Student Collection enhances the student learning experience in the specific course area related to the product. These specialized databases allow access to hundreds of scholarly and popular publications - all reliable sources - including journals, encyclopedias, and academic reports. Learn more and access at: http://gocengage.com/infotrac.
  • There are nearly 200 new exercises and 40 new examples, most of which include real data or other information from published sources.
  • Section 8.3, on hypothesis testing based on categorical data, now contains a subsection on Fisher’s Exact Test that is a useful alternative when assumptions for the standard chi-squared test fail.
  • Section 11.6, on regression, now contains a subsection on the multiple logistic regression model that accommodates multiple predictor variables for a dichotomous response.

Learning Resource Bundles

Choose the textbook packaged with the resources that best meet your course and student needs. Contact your Learning Consultant for more information.

Bundle: Text + Student Solutions Manual

ISBN-10: 1133798292 | ISBN-13: 9781133798293

List Price = $284.95  | CengageBrain Price = $284.95


Supplements

All supplements have been updated in coordination with the main title. Select the main title's "About" tab, then select "What's New" for updates specific to title's edition.

For more information about these supplements, or to obtain them, contact your Learning Consultant.

Instructor Supplements

Complete Solutions Manual  (ISBN-10: 1133590535 | ISBN-13: 9781133590538)

Complete solutions to all the problems in the text.

Solution Builder  (ISBN-10: 1133492193 | ISBN-13: 9781133492191)

This online instructor database offers complete worked solutions to all exercises in the text, allowing you to create customized, secure solutions printouts (in PDF format) matched exactly to the problems you assign in class. Vist Cengage.com/solutionbuilder for more information.

Student Solutions Manual  (ISBN-10: 1133492185 | ISBN-13: 9781133492184)

Contains fully worked-out solutions to all of the odd-numbered exercises in the text, giving students a way to check their answers and ensure that they took the correct steps to arrive at an answer.

List Price = $96.95  | CengageBrain Price = $96.95  | College Bookstore Wholesale Price = $72.75

Student Supplements

Student Solutions Manual  (ISBN-10: 1133492185 | ISBN-13: 9781133492184)

Go beyond the answers—see what it takes to get there and improve your grade! This manual provides worked-out, step-by-step solutions to the odd-numbered problems in the text. This gives you the information you need to truly understand how these problems are solved.

List Price = $96.95  | CengageBrain Price = $96.95  | College Bookstore Wholesale Price = $72.75

Meet the Author

Author Bio

Jay L. Devore

Jay Devore is Professor Emeritus of Statistics at California Polytechnic State University. He earned his undergraduate degree in Engineering Science from the University of California at Berkeley, spent a year at the University of Sheffield in England, and finished his Ph.D. in statistics at Stanford University. Jay previously taught at the University of Florida and at Oberlin College and has had visiting appointments at Stanford, Harvard, the University of Washington, New York University, and Columbia University. From 1998 to 2006, he served as Chair of the Cal Poly Statistics Department. In addition to this book, Jay has written several other widely used statistics texts for engineers and scientists and a book in applied mathematical statistics. He recently coauthored a text in probability and stochastic processes. He is the recipient of a distinguished teaching award from Cal Poly, is a Fellow of the American Statistical Association, and has served several terms as an Associate Editor of the “Journal of the American Statistical Association.” In his spare time, he enjoys reading, cooking and eating good food, tennis, and travel to faraway places. He is especially proud of his wife, Carol, a retired elementary school teacher, his daughter Allison, who has held several high-level positions in nonprofit organizations in Boston and New York City, and his daughter Teresa, a high school teacher in Brooklyn.

Nicholas R. Farnum

Nicholas Farnum received his B.S. and Ph.D. in Mathematics from University of California at Irvine. He is currently a professor in the Information Systems and Decision Sciences Department at California State University, Fullerton. Professor Farnum has published several papers in applied and theoretical statistics and has also written texts in Quality Control and Forecasting. He is a member of the American Statistical Association and the Mathematical Association of America. In his spare time Professor Farnum enjoys cooking, playing music, and traveling.

Jimmy A. Doi

Jimmy Doi earned his B.A. in Mathematics (minors in Biology, Chemistry, Japanese) from California State University, Northridge. He earned his masters and Ph.D. in Statistics at North Carolina State University. Since receiving his doctorate Professor Doi has been on the faculty in the Statistics Department at California Polytechnic State University, San Luis Obispo. His research interests include biostatistics and categorical data analysis. He enjoys traveling, kayak fishing, long board surfing, and playing basketball with his current and former students. But his favorite moments are when he spends time with his wife Midori and daughter Alicia.