Applied Statistics for Engineers and Scientists

ISBN-10: 0534467199

ISBN-13: 9780534467197

Edition: 2nd 2005 (Revised)

List price: $333.95
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Description: This concise book for engineering and sciences students emphasizes modern statistical methodology and data analysis. APPLIED STATISTICS FOR ENGINEERS AND SCIENTISTS is ideal for one-term courses that cover probability only to the extent that it is needed for inference. The authors emphasize application of methods to real problems, with real examples throughout. The text is designed to meet ABET standards and has been updated to reflect the most current methodology and practice.

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Book details

List price: $333.95
Edition: 2nd
Copyright year: 2005
Publisher: Brooks/Cole
Publication date: 2/20/2004
Binding: Hardcover
Pages: 632
Size: 7.50" wide x 9.25" long x 1.25" tall
Weight: 2.398
Language: English

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 Statistics Department. In addition to this book, Jay has written several widely used engineering statistics texts 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, an ESL teacher in New York City.

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.

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
Numerical Summary Measures
Measures of Center
Measures of Variability
More Detailed Summary Quantities
Quantile Plots
Supplementary Exercises
Bibliography
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
Obtaining Data
Operational Definitions
Data from Sampling
Data from Experiments
Measurement Systems
Supplementary Exercises
Bibliography
Probability And Sampling Distributions
Chance Experiments
Probability Concepts
Conditional Probability and Independence
Random Variables
Sampling Distributions
Describing Sampling Distributions
Supplementary Exercises
Bibliography
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
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 �1-�2 Based on a Normal Population Distributions
Other Topics in Estimation (Optional)
Supplementary Exercises
Bibliography
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
The Analysis Of Variance
Terminology and Concepts
Single-Factor ANOVA
Interpreting ANOVA Results
Randomized Block Experiments
Supplementary Exercises
Bibliography
Experimental Design
Terminology and Concepts
Two-Factor Designs
Multifactor Designs
2k Designs
Fractional Factorial Designs
Supplementary Exercises
Bibliography
Inferential Methods In Regression And Correlation
Regression and Models Involving a Single Independent Variable
Inferences About the Slope Coefficient ”
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
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