Probability and Statistics for Engineering and Science

ISBN-10: 0534372813

ISBN-13: 9780534372811

Edition: 5th 2000

Authors: Jay L. (Jay L. Devore) Devore

List price: $114.95
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Book details

List price: $114.95
Edition: 5th
Copyright year: 2000
Publisher: Brooks/Cole
Publication date: 12/9/1999
Binding: Hardcover
Pages: 750
Size: 7.87" wide x 9.84" long
Weight: 3.388
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.

Overview and Descriptive Statisticsp. 1
Introductionp. 1
Populations, Samples, and Processesp. 3
Pictorial and Tabular Methods in Descriptive Statisticsp. 11
Measures of Locationp. 28
Measures of Variabilityp. 36
Supplementary Exercisesp. 48
Bibliographyp. 51
Probabilityp. 52
Introductionp. 52
Sample Spaces and Eventsp. 53
Axioms, Interpretations, and Properties of Probabilityp. 58
Counting Techniquesp. 67
Conditional Probabilityp. 75
Independencep. 86
Supplementary Exercisesp. 92
Bibliographyp. 96
Discrete Random Variables and Probability Distributionsp. 97
Introductionp. 97
Random Variablesp. 98
Probability Distributions for Discrete Random Variablesp. 101
Expected Values of Discrete Random Variablesp. 111
The Binomial Probability Distributionp. 120
Hypergeometric and Negative Binomial Distributionsp. 128
The Poisson Probability Distributionp. 135
Supplementary Exercisesp. 140
Bibliographyp. 144
Continuous Random Variables and Probability Distributionsp. 145
Introductionp. 145
Continuous Random Variables and Probability Density Functionsp. 146
Cumulative Distribution Functions and Expected Valuesp. 152
The Normal Distributionp. 160
The Gamma Distribution and Its Relativesp. 174
Other Continuous Distributionsp. 181
Probability Plotsp. 188
Supplementary Exercisesp. 199
Bibliographyp. 204
Joint Probability Distributions and Random Samplesp. 205
Introductionp. 205
Jointly Distributed Random Variablesp. 206
Expected Values, Covariance, and Correlationp. 219
Statistics and Their Distributionsp. 225
The Distribution of the Sample Meanp. 237
The Distribution of a Linear Combinationp. 243
Supplementary Exercisesp. 249
Bibliographyp. 252
Point Estimationp. 253
Introductionp. 253
Some General Concepts of Point Estimationp. 254
Methods of Point Estimationp. 269
Supplementary Exercisesp. 278
Bibliographyp. 279
Statistical Intervals Based on a Single Samplep. 281
Introductionp. 281
Basic Properties of Confidence Intervalsp. 282
Large-Sample Confidence Intervals for a Population Mean and Proportionp. 291
Intervals Based on a Normal Population Distributionp. 299
Confidence Intervals for the Variance and Standard Deviation of a Normal Populationp. 308
Supplementary Exercisesp. 311
Bibliographyp. 314
Tests of Hypotheses Based on a Single Samplep. 315
Introductionp. 315
Hypotheses and Test Proceduresp. 316
Tests About a Population Meanp. 326
Tests Concerning a Population Proportionp. 339
P-Valuesp. 344
Some Comments on Selecting a Test Procedurep. 352
Supplementary Exercisesp. 356
Bibliographyp. 359
Inferences Based on Two Samplesp. 354
Introductionp. 354
z Tests and Confidence Intervals for a Difference Between Two Population Meansp. 361
The Two-Sample t Test and Confidence Intervalp. 372
Analysis of Paired Datap. 381
Inferences Concerning a Difference Between Population Proportionsp. 391
Inferences Concerning Two Population Variancesp. 399
Supplementary Exercisesp. 403
Bibliographyp. 409
The Analysis of Variancep. 410
Introductionp. 410
Single-Factor ANOVAp. 411
Multiple Comparisons in ANOVAp. 422
More on Single-Factor ANOVAp. 428
Supplementary Exercisesp. 438
Bibliographyp. 440
Multifactor Analysis of Variancep. 441
Introductionp. 441
Two-Factor ANOVA with K[subscript ij] = 1p. 442
Two-Factor ANOVA with K[subscript ij] [greater than sign] 1p. 456
Three-Factor ANOVAp. 465
2[superscript p] Factorial Experimentsp. 476
Supplementary Exercisesp. 491
Bibliographyp. 494
Simple Linear Regression and Correlationp. 496
Introductionp. 496
The Simple Linear Regression Modelp. 497
Estimating Model Parametersp. 505
Inferences About the Slope Parameter beta[subscript 1]p. 520
Inferences Concerning [mu subscript Y[middle dot]x*] and the Prediction of Future Y Valuesp. 530
Correlationp. 538
Supplementary Exercisesp. 549
Bibliographyp. 554
Nonlinear and Multiple Regressionp. 555
Introductionp. 555
Aptness of the Model and Model Checkingp. 556
Regression with Transformed Variablesp. 564
Polynomial Regressionp. 576
Multiple Regression Analysisp. 587
Other Issues in Multiple Regressionp. 612
Supplementary Exercisesp. 626
Bibliographyp. 632
Goodness-of-Fit Tests and Categorical Data Analysisp. 633
Introductionp. 633
Goodness-of-Fit Tests When Category Probabilities Are Completely Specifiedp. 634
Goodness-of-Fit Tests for Composite Hypothesesp. 642
Two-Way Contingency Tablesp. 655
Supplementary Exercisesp. 663
Bibliographyp. 666
Distribution-Free Proceduresp. 667
Introductionp. 667
The Wilcoxon Signed-Rank Testp. 668
The Wilcoxon Rank-Sum Testp. 677
Distribution-Free Confidence Intervalsp. 684
Distribution-Free ANOVAp. 689
Supplementary Exercisesp. 693
Bibliographyp. 695
Quality Control Methodsp. 696
Introductionp. 696
General Comments on Control Chartsp. 697
Control Charts for Process Locationp. 699
Control Charts for Process Variationp. 708
Control Charts for Attributesp. 713
CUSUM Proceduresp. 718
Acceptance Samplingp. 727
Supplementary Exercisesp. 733
Bibliographyp. 734
Tablesp. 735
Cumulative Binomial Probabilitiesp. 736
Cumulative Poisson Probabilitiesp. 738
Standard Normal Curve Areasp. 740
The Incomplete Gamma Functionp. 742
Critical Values for t Distributionsp. 743
Tolerance Critical Values for Normal Population Distributionsp. 744
Critical Values for Chi-Squared Distributionsp. 745
t Curve Tail Areasp. 746
Critical Values for F Distributionsp. 748
Critical Values for Studentized Range Distributionsp. 754
Chi-Squared Curve Tail Areasp. 755
Critical Values for the Ryan-Joiner Test of Normalityp. 757
Critical Values for the Wilcoxon Signed-Rank Testp. 758
Critical Values for the Wilcoxon Rank-Sum Testp. 759
Critical Values for the Wilcoxon Signed-Rank Intervalp. 760
Critical Values for the Wilcoxon Rank-Sum Intervalp. 761
[beta] Curves for t Testsp. 762
Answers to Odd-Numbered Exercisesp. 763
Indexp. 785
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