Statistics for Engineers and Scientists stands out for its crystal clear presentation of applied statistics. Suitable for a one or two semester course, the book takes a practical approach to methods of statistical modeling and data analysis that are most often used in scientific work. Statistics for Engineers and Scientists features a unique approach highlighted by an engaging writing style that explains difficult concepts clearly, along with the use of contemporary real world data sets to help motivate students and show direct connections to industry and research. While focusing on practical applications of statistics, the text makes extensive use of examples to motivate fundamental concepts and to develop intuition.
Author(s): William Navidi
Edition: 3
Publisher: McGraw-Hill Science/Engineering/Math
Year: 2010
Language: English
Pages: 933
Tags: Математика;Теория вероятностей и математическая статистика;Математическая статистика;Прикладная математическая статистика;
Cover......Page 1
Title Page......Page 4
Copyright......Page 5
Contents......Page 10
Preface......Page 14
Acknowledgments of Reviewers and Contributors......Page 18
Key Features......Page 20
Supplements for Students and Instructors......Page 21
Introduction......Page 22
1.1 Sampling......Page 24
1.2 Summary Statistics......Page 34
1.3 Graphical Summaries......Page 46
2.1 Basic Ideas......Page 69
2.2 Counting Methods......Page 83
2.3 Conditional Probability and Independence......Page 90
2.4 Random Variables......Page 111
2.5 Linear Functions of Random Variables......Page 137
2.6 Jointly Distributed Random Variables......Page 148
3.1 Measurement Error......Page 185
3.2 Linear Combinations of Measurements......Page 191
3.3 Uncertainties for Functions of One Measurement......Page 201
3.4 Uncertainties for Functions of Several Measurements......Page 207
4.1 The Bernoulli Distribution......Page 221
4.2 The Binomial Distribution......Page 224
4.3 The Poisson Distribution......Page 236
4.4 Some Other Discrete Distributions......Page 251
4.5 The Normal Distribution......Page 262
4.6 The Lognormal Distribution......Page 277
4.7 The Exponential Distribution......Page 283
4.8 Some Other Continuous Distributions......Page 292
4.9 Some Principles of Point Estimation......Page 301
4.10 Probability Plots......Page 306
4.11 The Central Limit Theorem......Page 311
4.12 Simulation......Page 323
Introduction......Page 343
5.1 Large-Sample Confidence Intervals for a Population Mean......Page 344
5.2 Confidence Intervals for Proportions......Page 359
5.3 Small-Sample Confidence Intervals for a Population Mean......Page 365
5.4 Confidence Intervals for the Difference Between Two Means......Page 375
5.5 Confidence Intervals for the Difference Between Two Proportions......Page 379
5.6 Small-Sample Confidence Intervals for the Difference Between Two Means......Page 384
5.7 Confidence Intervals with Paired Data......Page 391
5.8 Prediction Intervals and Tolerance Intervals......Page 395
5.9 Using Simulation to Construct Confidence Intervals......Page 400
6.1 Large-Sample Tests for a Population Mean......Page 417
6.2 Drawing Conclusions from the Results of Hypothesis Tests......Page 426
6.3 Tests for a Population Proportion......Page 434
6.4 Small-Sample Tests for a Population Mean......Page 439
6.5 Large-Sample Tests for the Difference Between Two Means......Page 444
6.6 Tests for the Difference Between Two Proportions......Page 451
6.7 Small-Sample Tests for the Difference Between Two Means......Page 456
6.8 Tests with Paired Data......Page 465
6.9 Distribution-Free Tests......Page 471
6.10 The Chi-Square Test......Page 480
6.11 The F Test for Equality of Variance......Page 490
6.12 Fixed-Level Testing......Page 494
6.13 Power......Page 500
6.14 Multiple Tests......Page 509
6.15 Using Simulation to Perform Hypothesis Tests......Page 513
7.1 Correlation......Page 526
7.2 The Least-Squares Line......Page 544
7.3 Uncertainties in the Least-Squares Coefficients......Page 560
7.4 Checking Assumptions and Transforming Data......Page 581
8.1 The Multiple Regression Model......Page 613
8.2 Confounding and Collinearity......Page 631
8.3 Model Selection......Page 640
9.1 One-Factor Experiments......Page 679
9.2 Pairwise Comparisons in One-Factor Experiments......Page 704
9.3 Two-Factor Experiments......Page 717
9.4 Randomized Complete Block Designs......Page 742
9.5 2p Factorial Experiments......Page 752
10.1 Basic Ideas......Page 782
10.2 Control Charts for Variables......Page 785
10.3 Control Charts for Attributes......Page 805
10.4 The CUSUM Chart......Page 810
10.5 Process Capability......Page 814
Appendix A: Tables......Page 821
Appendix B: Partial Derivatives......Page 846
Appendix C: Bibliography......Page 848
Answers to Odd-Numbered Exercises......Page 851
Index......Page 919
