Statistics for engineering and the sciences

著者

書誌事項

Statistics for engineering and the sciences

William Mendenhall, Terry Sincich

Pearson Prentice-Hall, c2007

5th ed

大学図書館所蔵 件 / 全3件

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注記

Includes bibliographical references (p. 1028-1035) and index

内容説明・目次

内容説明

For engineering statistics courses in departments of Statistics and Engineering. This text is designed for a two-semester introductory course in statistics for students majoring in engineering or any of the physical sciences. Inevitalby, once these studenrts graduate and are employed, they will be involved in the collection and analysis of data and will be required to think critically about the results. Consequently, they need to acquire knowledge of the basic concepts of data description and statistical inference and familiarity with statistical methods they are required to use on the job.The text includes optional theoretical exercises allowing instructors who choose to emphasize theory to do so without requiring additional materials. The assumed mathematical background is a two-semester sequence in calculus - that is, the course could be taught to students of average mathematical talent and with a basic understanding of the principles of differential and integral calculus. Datasets and other resources (where applicable) for this book are available here.

目次

  • CHAPTER 1: INTRODUCTION 1.1 Statistics: The Science of Data 1.2 Fundamental Elements of Statistics 1.3 Types of Data 1.4 The Role of Statistics in Critical Thinking 1.5 A Guide to Statistical Methods Presented in this Text Statistics in Action: Contamination of Fish in the Tennessee River Collecting theData CHAPTER 2: DESCRIPTIVE STATISTICS 2.1 Graphical and Numerical Methods for Describing Qualitative Data 2.2 Graphical Methods for Describing Quantitative Data 2.3 Numerical Methods for Describing Quantitative Data 2.4 Measures of Central Tendency 2.5 Measures of Variation 2.6 Measures of Relative Standing 2.7 Methods for Detecting Outliers 2.8 Distorting the Truth with Descriptive Statistics Statistics in Action: Characteristics of Contaminated Fish in the Tennessee River CHAPTER 3: PROBABILITY 3.1 The Role of Probability in Statistics 3.2 Events, Sample Spaces, and Probability 3.3 Compound Events 3.4 Complementary Events 3.5 Conditional Probability 3.6 Probability Rules for Unions and Intersections 3.7 Bayes' Rule (Optional) 3.8 Some Counting Rules 3.9 Probability and Statistics: An Example 3.10 Random Sampling Statistics in Action: Assessing Predictors of Software Defects CHAPTER 4: DISCRETE RANDOM VARIABLES 4.1 Discrete Random Variables 4.2 The Probability Distribution for a Discrete Random Variable 4.3 Expected Values for Random Variables 4.4 Some Useful Expectation Theorems 4.5 Bernoulli Trials 4.6 The Binomial Probability Distribution 4.7 The Multinomial Probability Distribution 4.8 The Negative Binomial and the Geometric Probability Distributions 4.9 The Hypergeometric Probability Distribution 4.10 The Poisson Probability Distribution 4.11 Moments and Moment Generating Functions (Optional) Statistics in Action: The Reliability of a "One-Shot" Device CHAPTER 5: CONTINUOUS RANDOM VARIABLES 5.1 Continuous Random Variables 5.2 The Density Function for a Continuous Random Variable 5.3 Expected Values for Continuous Random Variables 5.4 The Uniform Probability Distribution 5.5 The Normal Probability Distribution 5.6 Descriptive Methods for Assessing Normality 5.7 Gamma-Type Probability Distributions 5.8 The Weibull Probability Distriibution 5.9 Beta-Type Probability Distributions 5.10 Moments and Moment Generating Functions (Optional) Statistics in Action: Super Weapons Development: Optimizing the Hit Ratio CHAPTER 6: JOINT PROBABILITY DISTRIBUTIONS AND SAMPLING DISTRIBUTIONS 6.1 Bivariate Probability Distributions for Discrete Random Variables 6.2 Bivariate Probability Distributions for Continuous Random Variables 6.3 The Expected Value of Functions of Two Random Variables 6.4 Independence 6.5 The Covariance and Correlation of Two Random Variables 6.6 Probability Distributions and Expected Values of Functions of Random Variables (Optional) 6.7 Sampling Distributions 6.8 Approximating a Sampling Distribution by Monte Carlo Simulation 6.9 The Sampling Distributions of Means and Sums 6.10 Normal Approximation to the Binomial Distribution 6.11 Sampling Distributions Related to the Normal Distribution Statistics in Action: Availability of an Up/Down System CHAPTER 7: ESTIMATION USING CONFIDENCE INTERVALS 7.1 Point Estimators and their Properties 7.2 Finding Point Estimators: Classical Methods of Estimation 7.3 Finding Interval Estimators: The Pivotal Method 7.4 Estimation of Population Mean 7.5 Estimation of the Difference Between Two Population Means: Independent Samples 7.6 Estimation of the Difference Between Two Population Means: Matched Pairs 7.7 Estimation of a Poulation Proportion 7.8 Estimation of the Difference Between Two Population Proportions 7.9 Estimation of a Population Variance 7.10 Estimation of the Ratio of Two Population Variances 7.11 Choosing the Sample Size 7.12 Alternative Estimation Methods: Bootstrapping and Bayesian Methods (Optional) Statistics in Action: Bursting Strength of PET Beverage Bottles CHAPTER 8: TESTS OF HYPOTHESES 8.1 The Relationship Between Statistical Tests of Hypotheses and Confidence Intervals 8.2 Elements and Properties of a Statistical Test 8.3 Finding Statistical Tests: Classical Methods 8.4 Choosing the Null and Alternative Hypotheses 8.5 Testing a Population Mean 8.6 The Observed Significance Level for a Test 8.7 Testing the Difference Between Two Population Means: Independent Samples 8.8 Testing the Difference Between Two Population Means: Independent Samples 8.9 Testing a Population Proportion 8.10 Testing the Difference Between Two Population Proportions 8.11 Testing a Population Variance 8.12 Testing the Ration of Two Population Variances 8.13 Alternative Testing Procedures: Bootstrapping and Bayesian Methods (Optional) Statistics in Action: Comparing Methods for Dissolving Drug Tablets - Dissolution Method Equivalence Testing CHAPTER 9: CATEGORICAL DATA ANALYSIS 9.1 Categorical Data and Multinomial Probabilities 9.2 Estimating Category Probabilities in a One-Way Table 9.3 Testing Category Probabilities in a One-Way Table 9.4 Inferences About Category Probabilities in a Two-Way (Contingency) Table 9.5 Contingency Tables with Fixed Marginal Totals 9.6 Exact Tests for Independence in a Contingency Table Analysis (Optional) Statistics in Action: The Public's Perception of Engineers and Engineering CHAPTER 10: SIMPLE LINEAR REGRESSION 10.1 Regression Models 10.2 Model Assumptions 10.3 Estimating ss0 and ss1: The Method of Least Squares 10.4 Properties of the Least Squares Estimators 10.5 An Estimator of d2 10.6 Assessing the Utility of the Model: Making Inferences About the Slope ss1 10.7 The Coefficient of Correlation 10.8 The Coefficient of Determination 10.9 Using the Model for Estimation and Pediction 10.10 A Complete Example 10.11 A Summary of the Steps to Follow in Simple Linear Regression Statistics in Action: Can Dowser's Really Detect Water? CHAPTER 11: MULTIPLE REGRESSION ANALYSIS 11.1 General Form of a Multiple Regression Model 11.2 Model Assumptions 11.3 Fitting the Model: The Method of Least Squares 11.4 Computations using Matrix Algebra
  • Estimating and Making Inferences about the ss Parameters 11.5 Assessing Overall Model Adequacy 11.6 A Confidence Interval for E(y) and a prediction interval for a Future Value of y 11.7 A First-Order Model with Quantitative Predictors 11.8 An Interaction Model with Quantitative Predictors 11.9 A Quadratic (Second-Order) Model with a Quantitative Predictor 11.10 Checking Assumptions: Residual Analysis 11.11 Some Pitfalls: Estimability, Multicollinearity, and Extrapolation 11.12 A Summary of the Steps to Follow in a Multiple Regression Analysis Statistics in Action: Bid-Rigging in the Highway Construction Industry CHAPTER 12: MODEL BUILDING 12.1 Introduction: Why Model Building is Important 12.2 The Two Types of Independent Variables: Quantitative and Qualitative 12.3 Models with a Single Quantitative Independent Variable 12.4 Models with Two Quantitative Independent Variables 12.5 Coding Quantitative Independent Variables (Optional) 12.6 Models with One Qualitative Independent Variable 12.7 Models with Both Quantitative and Qualitative Independent Variables 12.8 Tests for Comparing Nested Models 12.9 External Model Validation (Optional) 12.10 Stepwise Regression Statistics in Action: Deregulation of the Intrastate Trucking Industry CHAPTER 13: PRINCIPLES OF EXPERIMENTAL DESIGN 13.1 Introduction 13.2 Experimental Design Terminology 13.3 Controlling the Information in an Experiment 13.4 Noise-Reducing Designs 13.5 Volume-Increasing Designs 13.6 Selecting the Sample Size 13.7 The Importance of Randomization Statistics in Action: Anti-Corrosive Behavior of Epoxy Coatings Augmented with Zinc CHAPTER 14: ANALYSIS OF VARIANCE FOR DESIGNED EXPERIMENTS 14.1 Introduction 14.2 The Logic Behind an Analysis of Variance 14.3 One-Factor Completely Randomized Designs 14.4 Randomized Block Designs 14.5 Two-Factor Factorial Experiments 14.6 More Complex Factorial Designs (Optional) 14.7 Nested Sampling Designs (Optional) 14.8 Multiple Comparisons of Teatment Means 14.9 Checking ANOVA Assumptions Statistics in Action: On the Trail of the Cockroach CHAPTER 15: NONPARAMETRIC STATISTICS 15.1 Introduction: Distribution-Free Tests 15.2 Testing for Location of a Single Population 15.3 Comparing Two Populations: Independent Random Samples 15.4 Comparing Two Populations: Matched-Pair Design 15.5 Comparing Three or More Populations: Completely Randomized Design 15.6 Comparing Three or More Populations: Randomized Block Design 15.7 Nonparametric Regression Statistics in Action: Agent Orange and Vietnam Vets CHAPTER 16: STATISTICAL PROCESS AND QUALITY CONTROL 16.1 Total Quality Management 16.2 Variable Control Charts 16.3 Control Chart for Means: x-Chart 16.4 Control Chart for Process Variation: R-Chart 16.5 Detecting Trends in a Control Chart: Runs Analysis 16.6 Control Chart for Percent Defective: p-Chart 16.7 Control Chart for number of Defectives per item: c-Chart 16.8 Tolerance Limits 16.9 Capability Analysis (Optional) 16.10 Acceptance Sampling for Defectives 16.11 Other Sampling Plans (Optional) 16.12 Evolutionary Operations (Optional) Statistics in Action: Testing Jet Fuel Additive for Safety CHAPTER 17: PRODUCT AND SYSTEM RELIABILITY 17.1 Introduction 17.2 Failure Time Distributions 17.3 Hazard Rates 17.4 Life Testing: Censored Sampling 17.5 Estimating the Parameters of an Exponential Failure Time Distribution 17.6 Estimating the Parameters of a Weibull Failure Time Distribution 17.7 System Reliability Statistics in Action: Modeling the Hazard Rate of Reinforced Concrete Bridge Deck Deterioration APPENDIX A: MATRIX ALGEBRA APPENDIX B: USEFUL STATISTICAL TABLES APPENDIX C: SAS FOR WINDOWS TUTORIAL APPENDIX D: MINITAB FOR WINDOWS TUTORIAL APPENDIX E: SPSS FOR WINDOWS TUTORIAL ANSWERS TO SELECTED EXERCISES INDEX

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