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正版 工程师与科学家统计学:英文 威廉·耐威迪 哈尔滨工业大学出
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Preface
Acknowledgments of Reviewers and Contributors
Key Features
Supplements for Students and Instructors
Chapter 1 Sampling and Descriptive Statistics Introduction
1.1 Sampling
1.2 Summary Statistics
1.3 Graphical Summaries
Chapter 2 Probability
Introduction
2.1 Basicldeas
2.2 Counting Methods
2.3 Conditional Probability and Independence
2.4 Random Variables
2.5 Linear Functions of Random Variables
2.6 Jointly Distributed Random Variables
Chapter 3 Propagation of Error Introduction
3.1 Measurement Error
3.2 Linear Combinations of Measurements
3.3 Uncertainties for Functions of One Measurement
3.4 Uncertainties for Functions of Several Measurements
Chapter 4 Commonly Used Distributions
Introduction
4.1 The Bernoulli Distribution
4,2 The Binomial Distribution
4,3 The Poisson Distribution
4.4 Some Other Discrete Distributions
4.5 The Normal Distribution
4.6 The Lognormal Distribution
4.7 The Exponential Distribution
4.8 Some Other Continuous Distributions
4.9 Some Principles of Point Estimation
4.10 Probability Plots
4.11 The Central Limit Theorem
4.12 Simulation
Chapter 5 Confidencelntervals Introduction
5.1 Large-Sample Confidence Intervals
for a Population Mean
5.2 Confidence Intervals for Proportions
5.3 Small-Sample Confidence Intervals for a Population Mean
……
Chapter 6 Hypothesis Testing
Chapter 7 Correlation and Simple Linear Regression
Chapter 8 Multiple Regression
Chapter 9 Factorial Experiments
Chapter 10 Statistical Quality Control
Appendix A:Tables 804.
Appendix B: PartiaI Derivatives
Appendix C: Bibliography
Answers to Odd-Numbered Exercises
Index
编辑手记
William Navidi is Professor of Applied Mathematics and Statistics at the Colorado School of Mines.He received his B.A. degree in mathematics from New College, his M.A. in mathematics from Michigan State University,and his Ph.D. in statistics from the University of California at Berkeley. Professor Navidi has authored more than 70 research papers both in statistical theory and in a wide variety of applications includ-ing computer networks, epidemiology, molecular biology, chemical engineering, and geophysics.
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