Statistics for engineering and the sciences / William Mendenhall, Terry Sincich.

By:

Mendenhall, William

Contributor(s):

Sincich, Terry

Material type: Text

TextPublication details: Upper Saddle River, N.J. : Pearson Prentice-Hall, c2007.Edition: 5th edDescription: xii, 1060 p. : ill. ; 26 cmISBN:

0131877062
9780131877061

Subject(s):

DDC classification:

519.5 MEN

Holdings
Item type	Current library	Call number	Copy number	Status	Date due	Barcode
Standard Loan	Moylish Library Main Collection	519.5 MEN (Browse shelf(Opens below))	0	Available		39002100447334
Standard Loan	Moylish Library Main Collection	519.5 MEN (Browse shelf(Opens below))	1	Missing		39002100357368

Enhanced descriptions from Syndetics:

This text is designed for a two-semester introductory course in statistics for students majoring in engineering or any of the physical sciences. Inevitably, once these students 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.

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

Table of contents provided by Syndetics

Preface (p. ix)
Chapter 1 Introduction (p. 1)
1.1 Statistics: The Science of Data (p. 2)
1.2 Fundamental Elements of Statistics (p. 2)
1.3 Types of Data (p. 5)
1.4 The Role of Statistics in Critical Thinking (p. 7)
1.5 A Guide to Statistical Methods Presented in This Text (p. 9)
Statistics in Action: Contamination of Fish in the Tennessee River: Collecting the Data (p. 10)
Chapter 2 Descriptive Statistics (p. 12)
2.1 Graphical and Numerical Methods for Describing Qualitative Data (p. 13)
2.2 Graphical Methods for Describing Quantitative Data (p. 19)
2.3 Numerical Methods for Describing Quantitative Data (p. 27)
2.4 Measures of Central Tendency (p. 28)
2.5 Measures of Variation (p. 32)
2.6 Measures of Relative Standing (p. 38)
2.7 Methods for Detecting Outliers (p. 41)
2.8 Distorting the Truth with Descriptive Statistics (p. 45)
Statistics in Action: Characteristics of Contaminated Fish in the Tennessee River, Alabama (p. 56)
Chapter 3 Probability (p. 59)
3.1 The Role of Probability in Statistics (p. 60)
3.2 Events, Sample Spaces, and Probability (p. 60)
3.3 Compound Events (p. 70)
3.4 Complementary Events (p. 72)
3.5 Conditional Probability (p. 76)
3.6 Probability Rules for Unions and Intersections (p. 80)
3.7 Bayes' Rule (Optional) (p. 90)
3.8 Some Counting Rules (p. 93)
3.9 Probability and Statistics: An Example (p. 103)
3.10 Random Sampling (p. 105)
Statistics in Action: Assessing Predictors of Software Defects in NASA Spacecraft Instrument Code (p. 114)
Chapter 4 Discrete Random Variables (p. 117)
4.1 Discrete Random Variables (p. 118)
4.2 The Probability Distribution for a Discrete Random Variable (p. 118)
4.3 Expected Values for Random Variables (p. 123)
4.4 Some Useful Expectation Theorems (p. 127)
4.5 Bernoulli Trials (p. 129)
4.6 The Binomial Probability Distribution (p. 130)
4.7 The Multinomial Probability Distribution (p. 137)
4.8 The Negative Binomial and the Geometric Probability Distributions (p. 142)
4.9 The Hypergeometric Probability Distribution (p. 146)
4.10 The Poisson Probability Distribution (p. 151)
4.11 Moments and Moment Generating Functions (Optional) (p. 157)
Statistics in Action: The Reliability of a "One-Shot" Device (p. 165)
Chapter 5 Continuous Random Variables (p. 168)
5.1 Continuous Random Variables (p. 169)
5.2 The Density Function for a Continuous Random Variable (p. 170)
5.3 Expected Values for Continuous Random Variables (p. 172)
5.4 The Uniform Probability Distribution (p. 177)
5.5 The Normal Probability Distribution (p. 180)
5.6 Descriptive Methods for Assessing Normality (p. 184)
5.7 Gamma-Type Probability Distributions (p. 190)
5.8 The Weibull Probability Distribution (p. 194)
5.9 Beta-Type Probability Distributions (p. 197)
5.10 Moments and Moment Generating Functions (Optional) (p. 200)
Statistics in Action: Super Weapons Development-Optimizing the Hit Ratio (p. 206)
Chapter 6 Bivariate Probability Distributions and Sampling Distributions (p. 211)
6.1 Bivariate Probability Distributions for Discrete Random Variables (p. 212)
6.2 Bivariate Probability Distributions for Continuous Random Variables (p. 217)
6.3 The Expected Value of Functions of Two Random Variables (p. 221)
6.4 Independence (p. 223)
6.5 The Covariance and Correlation of Two Random Variables (p. 225)
6.6 Probability Distributions and Expected Values of Functions of Random Variables (Optional) (p. 228)
6.7 Sampling Distributions (p. 236)
6.8 Approximating a Sampling Distribution by Monte Carlo Simulation (p. 237)
6.9 The Sampling Distributions of Means and Sums (p. 240)
6.10 Normal Approximation to the Binomial Distribution (p. 245)
6.11 Sampling Distributions Related to the Normal Distribution (p. 248)
Statistics in Action: Availability of an Up/Down Maintained System (p. 259)
Chapter 7 Estimation Using Confidence Intervals (p. 262)
7.1 Point Estimators and their Properties (p. 263)
7.2 Finding Point Estimators: Classical Methods of Estimation (p. 267)
7.3 Finding Interval Estimators: The Pivotal Method (p. 274)
7.4 Estimation of a Population Mean (p. 281)
7.5 Estimation of the Difference Between Two Population Means: Independent Samples (p. 287)
7.6 Estimation of the Difference Between Two Population Means: Matched Pairs (p. 294)
7.7 Estimation of a Population Proportion (p. 299)
7.8 Estimation of the Difference Between Two Population Proportions (p. 302)
7.9 Estimation of a Population Variance (p. 305)
7.10 Estimation of the Ratio of Two Population Variances (p. 309)
7.11 Choosing the Sample Size (p. 315)
7.12 Alternative Interval Estimation Methods: Bootstrapping and Bayesian Methods (Optional) (p. 318)
Statistics in Action: Bursting Strength of PET Beverage Bottles (p. 332)
Chapter 8 Tests of Hypotheses (p. 335)
8.1 The Relationship Between Statistical Tests of Hypotheses and Confidence Intervals (p. 336)
8.2 Elements and Properties of a Statistical Test (p. 336)
8.3 Finding Statistical Tests: Classical Methods (p. 342)
8.4 Choosing the Null and Alternative Hypotheses (p. 346)
8.5 Testing a Population Mean (p. 348)
8.6 The Observed Significance Level for a Test (p. 354)
8.7 Testing the Difference Between Two Population Means: Independent Samples (p. 357)
8.8 Testing the Difference Between Two Population Means: Matched Pairs (p. 364)
8.9 Testing a Population Proportion (p. 369)
8.10 Testing the Difference Between Two Population Proportions (p. 372)
8.11 Testing a Population Variance (p. 376)
8.12 Testing the Ratio of Two Population Variances (p. 379)
8.13 Alternative Testing Procedures: Bootstrapping and Bayesian Methods (Optional) (p. 383)
Statistics in Action: Comparing Methods for Dissolving Drug Tablets-Dissolution Method Equivalence Testing (p. 395)
Chapter 9 Categorical Data Analysis (p. 400)
9.1 Categorical Data and Multinomial Probabilities (p. 401)
9.2 Estimating Category Probabilities in a One-Way Table (p. 401)
9.3 Testing Category Probabilities in a One-Way Table (p. 405)
9.4 Inferences About Category Probabilities in a Two-Way (Contingency) Table (p. 409)
9.5 Contingency Tables with Fixed Marginal Totals (p. 417)
9.6 Exact Tests for Independence in a Contingency Table Analysis (Optional) (p. 422)
Statistics in Action: The Public's Perception of Engineers and Engineering (p. 432)
Chapter 10 Simple Linear Regression (p. 439)
10.1 Regression Models (p. 440)
10.2 Model Assumptions (p. 441)
10.3 Estimating [beta subscript 0] and [beta subscript 1]: The Method of Least Squares (p. 443)
10.4 Properties of the Least Squares Estimators (p. 454)
10.5 An Estimator of [sigma superscript 2] (p. 456)
10.6 Assessing the Utility of the Model: Making Inferences About the Slope [beta subscript 1] (p. 460)
10.7 The Coefficient of Correlation (p. 465)
10.8 The Coefficient of Determination (p. 469)
10.9 Using the Model for Estimation and Prediction (p. 473)
10.10 A Complete Example (p. 480)
10.11 A Summary of the Steps to Follow in Simple Linear Regression (p. 483)
Statistics in Action: Can Dowsers Really Detect Water? (p. 491)
Chapter 11 Multiple Regression Analysis (p. 495)
11.1 General Form of a Multiple Regression Model (p. 496)
11.2 Model Assumptions (p. 497)
11.3 Fitting the Model: The Method of Least Squares (p. 498)
11.4 Computations Using Matrix Algebra: Estimating and Making Inferences About the Individual [beta] Parameters (p. 499)
11.5 Assessing Overall Model Adequacy (p. 506)
11.6 A Confidence Interval for E(y) and a Prediction Interval for a Future Value of y (p. 510)
11.7 A First-Order Model with Quantitative Predictors (p. 519)
11.8 An Interaction Model with Quantitative Predictors (p. 528)
11.9 A Quadratic (Second-Order) Model with a Quantitative Predictor (p. 533)
11.10 Checking Assumptions: Residual Analysis (p. 540)
11.11 Some Pitfalls: Estimability, Multicollinearity, and Extrapolation (p. 559)
11.12 A Summary of the Steps to Follow in a Multiple Regression Analysis (p. 568)
Statistics in Action: Bid-Rigging in the Highway Construction Industry (p. 575)
Chapter 12 Model Building (p. 583)
12.1 Introduction: Why Model Building Is Important (p. 584)
12.2 The Two Types of Independent Variables: Quantitative and Qualitative (p. 585)
12.3 Models with a Single Quantitative Independent Variable (p. 586)
12.4 Models with Two Quantitative Independent Variables (p. 593)
12.5 Coding Quantitative Independent Variables (Optional) (p. 600)
12.6 Models with One Qualitative Independent Variable (p. 605)
12.7 Models with Both Quantitative and Qualitative Independent Variables (p. 611)
12.8 Tests for Comparing Nested Models (p. 621)
12.9 External Model Validation (Optional) (p. 628)
12.10 Stepwise Regression (p. 630)
Statistics in Action: Deregulation of the Intrastate Trucking Industry (p. 640)
Chapter 13 Principles of Experimental Design (p. 648)
13.1 Introduction (p. 649)
13.2 Experimental Design Terminology (p. 649)
13.3 Controlling the Information in an Experiment (p. 651)
13.4 Noise-Reducing Designs (p. 652)
13.5 Volume-Increasing Designs (p. 658)
13.6 Selecting the Sample Size (p. 663)
13.7 The Importance of Randomization (p. 665)
Statistics in Action: Anticorrosive Behavior of Epoxy Coatings Augmented with Zinc (p. 668)
Chapter 14 The Analysis of Variance for Designed Experiments (p. 671)
14.1 Introduction (p. 672)
14.2 The Logic Behind an Analysis of Variance (p. 672)
14.3 One-Factor Completely Randomized Designs (p. 674)
14.4 Randomized Block Designs (p. 685)
14.5 Two-Factor Factorial Experiments (p. 698)
14.6 More Complex Factorial Designs (Optional) (p. 714)
14.7 Nested Sampling Designs (Optional) (p. 721)
14.8 Multiple Comparisons of Treatment Means (p. 732)
14.9 Checking ANOVA Assumptions (p. 739)
Statistics in Action: On the Trail of the Cockroach (p. 751)
Chapter 15 Nonparametric Statistics (p. 755)
15.1 Introduction: Distribution-Free Tests (p. 756)
15.2 Testing for Location of a Single Population (p. 757)
15.3 Comparing Two Populations: Independent Random Samples (p. 762)
15.4 Comparing Two Populations: Matched-Pairs Design (p. 769)
15.5 Comparing Three or More Populations: Completely Randomized Design (p. 775)
15.6 Comparing Three or More Populations: Randomized Block Design (p. 780)
15.7 Nonparametric Regression (p. 784)
Statistics in Action: Deadly Exposure: Agent Orange and Vietnam Vets (p. 796)
Chapter 16 Statistical Process and Quality Control (p. 800)
16.1 Total Quality Management (p. 801)
16.2 Variable Control Charts (p. 801)
16.3 Control Chart for Means: x-Chart (p. 806)
16.4 Control Chart for Process Variation: R-Chart (p. 814)
16.5 Detecting Trends in a Control Chart: Runs Analysis (p. 819)
16.6 Control Chart for Percent Defectives: p-Chart (p. 821)
16.7 Control Chart for the Number of Defectives per Item: c-Chart (p. 825)
16.8 Tolerance Limits (p. 829)
16.9 Capability Analysis (Optional) (p. 832)
16.10 Acceptance Sampling for Defectives (p. 839)
16.11 Other Sampling Plans (Optional) (p. 844)
16.12 Evolutionary Operations (Optional) (p. 845)
Statistics in Action: Testing Jet Fuel Additive for Safety (p. 851)
Chapter 17 Product and System Reliability (p. 857)
17.1 Introduction (p. 858)
17.2 Failure Time Distributions (p. 858)
17.3 Hazard Rates (p. 859)
17.4 Life Testing: Censored Sampling (p. 863)
17.5 Estimating the Parameters of an Exponential Failure Time Distribution (p. 864)
17.6 Estimating the Parameters of a Weibull Failure Time Distribution (p. 867)
17.7 System Reliability (p. 872)
Statistics in Action: Modeling the Hazard Rate of Reinforced Concrete Bridge Deck Deterioration (p. 879)
Appendix A Matrix Algebra (p. 882)
A.1 Matrices and Matrix Multiplication (p. 882)
A.2 Identity Matrices and Matrix Inversion (p. 886)
A.3 Solving Systems of Simultaneous Linear Equations (p. 889)
A.4 A Procedure for Inverting a Matrix (p. 891)
Appendix B Useful Statistical Tables (p. 896)
Table 1 Random Numbers (p. 897)
Table 2 Cumulative Binomial Probabilities (p. 901)
Table 3 Exponentials (p. 905)
Table 4 Cumulative Poisson Probabilities (p. 906)
Table 5 Normal Curve Areas (p. 908)
Table 6 Gamma Function (p. 909)
Table 7 Critical Values for Student's T (p. 910)
Table 8 Critical Values of x[superscript 2] (p. 911)
Table 9 Percentage Points of the F Distribution, [alpha] = .10 (p. 913)
Table 10 Percentage Points of the F Distribution, [alpha] = .05 (p. 915)
Table 11 Percentage Points of the F Distribution, [alpha] = .025 (p. 917)
Table 12 Percentage Points of the F Distribution, [alpha] = .01 (p. 919)
Table 13 Percentage Points of the Studentized Range q(p,v), [alpha] = .05 (p. 921)
Table 14 Percentage Points of the Studentized Range q(p,v), [alpha] = .01 (p. 923)
Table 15 Critical Values of T[subscript L] and T[subscript U] for the Wilcoxon Rank Sum Test: Independent Samples (p. 925)
Table 16 Critical Values of T[subscript 0] for the Wilcoxon Matched-Pairs Signed Rank Test (p. 926)
Table 17 Critical Values of Spearman's Rank Correlation Coefficient (p. 927)
Table 18 Critical Values of C for the Theil Zero-Slope Test (p. 928)
Table 19 Factors Used When Constructing Control Charts (p. 932)
Table 20 Values of K for Tolerance Limits for Normal Distributions (p. 933)
Table 21 Sample Size n for Nonparametric Tolerance Limits (p. 934)
Table 22 Sample Size Code Letters: MIL-STD-105D (p. 934)
Table 23 A Portion of the Master Table for Normal Inspection (Single Sampling): MIL-STD-105D (p. 935)
Appendix C SAS for Windows Tutorial (p. 936)
Appendix D MINITAB for Windows Tutorial (p. 965)
Appendix E SPSS for Windows Tutorial (p. 998)
References (p. 1028)
Selected Short Answers (p. 1036)
Credits (p. 1049)
Index (p. 1054)