Statistics for engineering and the sciences:
Gespeichert in:
| Hauptverfasser: | , |
|---|---|
| Format: | Buch |
| Sprache: | English |
| Veröffentlicht: |
Boca Raton ; London ; New York
CRC Press, Taylor & Francis Group
[2016]
|
| Ausgabe: | Sixth edition, version date: 20160302 |
| Schlagworte: | |
| Online-Zugang: | Inhaltsverzeichnis |
| Beschreibung: | xv, 1166 Seiten Illustrationen, Diagramme |
| ISBN: | 9781498728850 1498728855 |
Internformat
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| 245 | 1 | 0 | |a Statistics for engineering and the sciences |c William M. Mendenhall, Terry L. Sincich |
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| 264 | 1 | |a Boca Raton ; London ; New York |b CRC Press, Taylor & Francis Group |c [2016] | |
| 264 | 4 | |c © 2016 | |
| 300 | |a xv, 1166 Seiten |b Illustrationen, Diagramme | ||
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| adam_text | Titel: Statistics for engineering and the sciences
Autor: Mendenhall, William
Jahr: 2016
Contents i v
Contents
Preface ix
Chapter 1 introduction 1
STATISTICS IN ACTION DDT Contamination of Fish in the Tennessee River 2
1.1 Statistics: The Science of Data 2
1.2 Fundamental Elements of Statistics 3
1.3 Types of Data 6
1.4 Collecting Data: Sampling 8
1.5 The Role of Statistics in Critical Thinking 16
1.6 A Guide to Statistical Methods Presented in This Text 16
STATISTICS IN ACTION REVISITED DDT Contamination of Fish in the Tennessee
River—Identifying the Data Collection Method, Population, Sample,
and Types of Data 18
Chapter 2 Descriptive statistics 21
STATISTICS IN ACTION Characteristics of Contaminated Fish in the Tennessee
River, Alabama 22
2.1 Graphical and Numerical Methods for Describing Qualitative Data 22
2.2 Graphical Methods for Describing Quantitative Data 29
2.3 Numerical Methods for Describing Quantitative Data 39
2.4 Measures of Central Tendency 39
2.5 Measures of Variation 46
2.6 Measures of Relative Standing 52
2.7 Methods for Detecting Outliers 55
2.8 Distorting the Truth with Descriptive Statistics 60
STATISTICS IN ACTION REVISITED Characteristics of Contaminated Fish in the
Tennessee River, Alabama 65
Chapter 3 Probability 76
STATISTICS IN ACTION Assessing Predictors of Software Defects in NASA Spacecraft
Instrument Code 77
3.1 The Role of Probability in Statistics 78
3.2 Events, Sample Spaces, and Probability 78
3.3 Compound Events 88
3.4 Complementary Events 90
3.5 Conditional Probability 94
3.6 Probability Rules for Unions and Intersections 99
3.7 Bayes Rule (Optional) 109
3.8 Some Counting Rules 112
3.9 Probability and Statistics: An Example 123
STATISTICS IN ACTION REVISITED Assessing Predictors of Software Defects in NASA
Spacecraft Instrument Code 125
vi i Contents
Chapter 4 Discrete Random Variables 133
STATISTICS IN ACTION The Reliability of a One-Shot Device 134
4.1 Discrete Random Variables 134
4.2 The Probability Distribution for a Discrete Random Variable 135
4.3 Expected Values for Random Variables 140
4.4 Some Useful Expectation Theorems 144
4.5 Bernoulli Trials 146
4.6 The Binomial Probability Distribution 147
4.7 The Multinomial Probability Distribution 154
4.8 The Negative Binomial and the Geometrie Probability Distributions 159
4.9 The Hypergeometric Probability Distribution 164
4.10 The Poisson Probability Distribution 168
4.11 Moments and Moment Generating Functions (Optional) 175
STATISTICS IN ACTION REVISITED The Reliability of a One-Shot Device 178
Chapter 5 Continuous Random Variables 186
STATISTICS IN ACTION Super Weapons Development—Optimizing the Hit Ratio 187
5.1 Continuous Random Variables 187
5.2 The Density Function for a Continuous Random Variable 189
5.3 Expected Values for Continuous Random Variables 192
5.4 The Uniform Probability Distribution 197
5.5 The Normal Probability Distribution 200
5.6 Descriptive Methods for Assessing Normality 206
5.7 Gamma-Type Probability Distributions 212
5.8 The Weibull Probability Distribution 216
5.9 Beta-Type Probability Distributions 220
5.10 Moments and Moment Generating Functions (Optional) 223
STATISTICS IN action revisted Super Weapons Development—Optimizing the
Hit Ratio 225
Chapter 6 Bivariate Probability Distributions and Sampling
Distributions 234
STATISTICS IN ACTION Availability of an Up/Down Maintained System 235
6.1 Bivariate Probability Distributions for Discrete Random Variables 235
6.2 Bivariate Probability Distributions for Continuous Random Variables 241
6.3 The Expected Value of Functions of Two Random Variables 245
6.4 Independence 247
6.5 The Covariance and Correlation of Two Random Variables 250
6.6 Probability Distributions and Expected Values of Functions of
Random Variables (Optional) 253
6.7 Sampling Distributions 261
6.8 Approximating a Sampling Distribution by Monte Carlo Simulation 262
6.9 The Sampling Distributions of Means and Sums 265
6.10 Normal Approximation to the Binomial Distribution 271
6.11 Sampling Distributions Related to the Normal Distribution 274
STATISTICS IN ACTION REVISITED Availability of an Up/Down Maintained System 280
Contents ! vii
Chapter 7 Estimation using Confidence intervals 288
STATISTICS IN ACTION Bursting Strength of PET Beverage Bottles 289
7.1 Point Estimators and their Properties 289
7.2 Finding Point Estimators: Classical Methods of Estimation 294
7.3 Finding Interval Estimators: The Pivotal Method 301
7.4 Estimation of a Population Mean 308
7.5 Estimation of the Difference Between Two Population Means: Independent Samples 314
7.6 Estimation of the Difference Between Two Population Means: Matched Pairs 322
7.7 Estimation of a Population Proportion 329
7.8 Estimation of the Difference Between Two Population Proportions 331
7.9 Estimation of a Population Variance 336
7.10 Estimation of the Ratio of Two Population Variances 340
7.11 Choosing the Sample Size 346
7.12 Alternative Interval Estimation Methods: Bootstrapping and Bayesian
Methods (Optional) 350
STATISTICS IN ACTION REVISITED Bursting Strength of PET Beverage Bottles 355
Chapter 8 Tests of Hypotheses 368
STATISTICS IN ACTION Comparing Methods for Dissolving DrugTablets—Dissolution
Method Equivalence Testing 369
8.1 The Relationship Between Statistical Tests of Hypotheses and Confidence Intervals 370
8.2 Elements and Properties of a Statistical Test 370
8.3 Finding Statistical Tests: Classical Methods 376
8.4 Choosing the Null and Alternative Hypotheses 381
8.5 The Observed Significance Level for a Test 382
8.6 Testing a Population Mean 386
8.7 Testing the Difference Between Two Population Means: Independent Samples 393
8.8 Testing the Difference Between Two Population Means: Matched Pairs 402
8.9 Testing a Population Proportion 408
8.10 Testing the Difference Between Two Population Proportions 411
8.11 Testing a Population Variance 416
8.12 Testing the Ratio of Two Population Variances 420
8.13 Alternative Testing Procedures: Bootstrapping and Bayesian Methods (Optional) 426
STATISTICS IN ACTION REVISITED Comparing Methods for Dissolving Drug Tablets—
Dissolution Method Equivalence Testing 431
Chapter 9 Categorical Data Analysis 442
STATISTICS IN ACTION The Case of the Ghoulish Transplant Tissue - Who is
Responsible for Paying Damages? 443
9.1 Categorical Data and Multinomial Probabilities 444
9.2 Estimating Category Probabilities in a One-Way Table 444
9.3 Testing Category Probabilities in a One-Way Table 448
9.4 Inferences About Category Probabilities in a Two-Way (Contingency) Table 453
9.5 Contingency Tables with Fixed Marginal Totais 462
9.6 Exact Tests for Independence in a Contingency Table Analysis (Optional) 467
STATISTICS IN ACTION REVISITED The Case of the Ghoulish Transplant Tissue 473
viii i Contents
Chapter 10 Simple Linear Regression 482
STATISTICS IN ACTION Can Dowsers Really Detect Water? 483
10.1 Regression Models 484
10.2 Model Assumptions 485
10.3 Estimating ß0 and ß 1: The Method of Least Squares 488
10.4 Properties of the Least-Squares Estimators 500
10.5 An Estimator of er2 503
10.6 Assessing the Utility of the Model: Making Inferences About the Slope ß i 507
10.7 The Coefficients of Correlation and Determination 513
10.8 Using the Model for Estimation and Prediction 521
10.9 Checking the Assumptions: Residual Analysis 530
10.10 A Complete Example 541
10.11 A Summary of the Steps to Follow in Simple Linear Regression 546
STATISTICS IN ACTION REVISITED Can Dowsers Really Detect Water? 546
Chapter 11 Multiple Regression Analysis 556
STATISTICS IN ACTION Bid-Rigging in the Highway Construction Industry 557
11.1 General Form of a Multiple Regression Model 558
11.2 Model Assumptions 559
11.3 Fitting the Model: The Method of Least Squares 560
11.4 Computations Using Matrix Algebra: Estimating and Making Inferences About
the Individual ß Parameters 561
11.5 Assessing Overall Model Adequacy 568
11.6 A Confidence Interval for E(y) and a Prediction Interval for a Future Value of y 572
11.7 A First-Order Model with Quantitative Predictors 582
11.8 An Interaction Model with Quantitative Predictors 592
11.9 A Quadratic (Second-Order) Model with a Quantitative Predictor 597
11.10 Regression Residuais and Outliers 605
11.11 Some Pitfalls: Estimability, Multicollinearity, and Extrapolation 617
11.12 A Summary of the Steps to Follow in a Multiple Regression Analysis 626
STATISTICS IN ACTION REVISITED Building a Model for Road Construction Costs in a
Sealed Bid Market 627
Chapter 12 Model Building 642
STATISTICS IN ACTION Deregulation of the Intrastate Trucking Industry 643
12.1 Introduction: Why Model Building Is Important 644
12.2 The Two Types of Independent Variables: Quantitative and Qualitative 645
12.3 Models with a Single Quantitative Independent Variable 647
12.4 Models with Two or More Quantitative Independent Variables 654
12.5 Coding Quantitative Independent Variables (Optional) 662
12.6 Models with One Qualitative Independent Variable 667
12.7 Models with Both Quantitative and Qualitative Independent Variables 674
12.8 Tests for Comparing Nested Models 685
12.9 External Model Validation (Optional) 692
12.10 Stepwise Regression 694
statistics IN ACTION REVISITED Deregulation in the Intrastate Trucking industry 701
Contents ix
Chapter 13 Principles of Experimental Design 716
STATISTICS IN ACTION Anti-corrosive Behavior of Epoxy Coatings Augmented
withZinc 717
13.1 Introduction 718
13.2 Experimental Design Terminology 718
13.3 Controlling the Information in an Experiment 720
13.4 Noise-Reducing Designs 721
13.5 Volume-Increasing Designs 728
13.6 Selecting the Sample Size 733
13.7 The Importance of Randomization 736
STATISTICS IN ACTION REVISITED Anti-Corrosive Behavior of Epoxy Coatings
Augmented with Zinc 736
Chapter 14 The Analysis of Variance for Designed Experiments 742
STATISTICS IN ACTION Pollutants at a Housing Development—A Case of Mishandling
Small Samples 743
14.1 Introduction 743
14.2 The Logic Behind an Analysis of Variance 744
14.3 One-Factor Completely Randomized Designs 746
14.4 Randomized Block Designs 758
14.5 Two-Factor Factorial Experiments 772
14.6 More Complex Factorial Designs (Optional) 791
14.7 Nested Sampling Designs (Optional) 799
14.8 Multiple Comparisons of Treatment Means 810
14.9 Checking ANOVA Assumptions 817
STATISTICS IN ACTION REVISTED Pollutants at a Housing Development—A Case of
Mishandling Small Samples 821
Chapter 15 Nonparametric Statistics 837
STATISTICS IN ACTION How Vulnerable Are New Hampshire Wells to Groundwater
Contamination? 838
15.1 Introduction: Distribution-Free Tests 839
15.2 Testing for Location of a Single Population 840
15.3 Comparing Two Populations: Independent Random Samples 845
15.4 Comparing Two Populations: Matched-Pairs Design 853
15.5 Comparing Three or More Populations: Completely Randomized Design 859
15.6 Comparing Three or More Populations: Randomized Block Design 864
15.7 Nonparametric Regression 869
STATISTICS IN ACTION REVISITED How Vulnerable are New Hampshire Wells to
Groundwater Contamination? 876
Chapter 16 Statistical Process and Quality Control 888
STATISTICS IN ACTION Testing Jet Fuel Additive for Safety 889
16.1 Total Quality Management 890
16.2 Variable Control Charts 890
16.3 Control Chart for Means: x-Chart 896
16.4 Control Chart for Process Variation: R-Chart 904
x I Contents
16.5 Detecting Trends in a Control Chart: Runs Analysis 910
16.6 Control Chart for Percent Defectives: p-Chaxt 912
16.7 Control Chart for the Number of Defects per Item: c-Chart 917
16.8 Tolerance Limits 921
16.9 Capability Analysis (Optional) 925
16.10 Acceptance Sampling for Defectives 933
16.11 Other Sampling Plans (Optional) 937
16.12 Evolutionary Operations (Optional) 938
STATISTICS IN ACTION REVISITED Testing Jet Fuel Additive for Safety 939
Chapter 17 Product and System Reliability 951
STATISTICS IN ACTION Modeling the Hazard Rate of Reinforced Concrete Bridge
Deck Deterioration 952
17.1 Introduction 952
17.2 Failure Time Distributions 952
17.3 Hazard Rates 954
17.4 Life Testing: Censored Sampling 958
17.5 Estimating the Parameters of an Exponential Failure Time Distribution 959
17.6 Estimating the Parameters of a Weibull Failure Time Distribution 962
17.7 System Reliability 967
STATISTICS IN ACTION REVISITED Modeling the Hazard Rate of Reinforced Concrete
Bridge Deck Deterioration 971
Appendix A Matrix Algebra 977
A. 1 Matrices and Matrix Multiplication 977
A.2 Identity Matrices and Matrix Inversion 981
A.3 Solving Systems of Simultaneous Linear Equations 984
A.4 A Procedure for Inverting a Matrix 986
Appendix B Useful Statistical Tables 991
TABLE 1 Random Numbers 992
TABLE 2 Cumulative Binomial Probabilities 996
TABLE 3 Exponentials 1000
TABLE 4 Cumulative Poisson Probabilities 1001
TABLE 5 Normal Curve Areas 1003
TABLE 6 Gamma Function 1004
TABLE 7 Critical Values for Student s T 1005
TABLE 8 Critical Values of x2 1006
TABLE 9 Percentage Points of the F Distribution, a = . 10 1008
TABLE 10 Percentage Points of the F Distribution, a = .05 1010
TABLE 11 Percentage Points of the F Distribution, a = .025 1012
TABLE 12 Percentage Points of the F Distribution, a = .01 1014
TABLE 13 Percentage Points of the Studentized Range q(p, v),a = .05 1016
TABLE 14 Percentage Points of the Studentized Range q(p, v), a = .01 1018
TABLE 15 Critical Values of Th and Tv for the Wilcoxon Rank Sum Test:
Independent Samples 1020
Contents ; xi
TABLE 16 Critical Values of T0 in the Wilcoxon Matched-Pairs Signed Rank Test 1021
TABLE 17 Critical Values of Spearman s Rank Correlation Coefficient 1022
TABLE 18 Critical Values of C for the Theil Zero-Slope Test 1023
TABLE 19 Factors Used When Constructing Control Charts 1027
TABLE 20 Values of K for Tolerance Limits for Normal Distributions 1028
TABLE 22 Sample Size Code Letters: MIL-STD-105D 1029
TABLE 21 Sample Size n for Nonparametric Tolerance Limits 1029
TABLE 23 A Portion of the Master Table for Normal Inspection (Single Sampling):
MIL-STD-105D 1030
Appendix C SAS for Windows Tutorial 1031
APPENDIX D MlNlTAB for Windows Tutorial 1062
APPENDIX E SPSS for Windows Tutorial 1094
References 1125
selected Short Answers 1133
Credits 1147
index 1152
|
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| id | DE-604.BV043018726 |
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| indexdate | 2024-08-01T11:25:14Z |
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| isbn | 9781498728850 1498728855 |
| language | English |
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| publishDate | 2016 |
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| subject_GND | (DE-588)4056995-0 (DE-588)4026955-3 |
| title | Statistics for engineering and the sciences |
| title_auth | Statistics for engineering and the sciences |
| title_exact_search | Statistics for engineering and the sciences |
| title_full | Statistics for engineering and the sciences William M. Mendenhall, Terry L. Sincich |
| title_fullStr | Statistics for engineering and the sciences William M. Mendenhall, Terry L. Sincich |
| title_full_unstemmed | Statistics for engineering and the sciences William M. Mendenhall, Terry L. Sincich |
| title_short | Statistics for engineering and the sciences |
| title_sort | statistics for engineering and the sciences |
| topic | Statistik (DE-588)4056995-0 gnd Ingenieur (DE-588)4026955-3 gnd |
| topic_facet | Statistik Ingenieur |
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