Applied statistics and probability for engineers / Douglas C. Montgomery, George C. Runger.

By: Montgomery, Douglas C [author.].

Contributor(s): Runger, George C .

Material type: materialTypeLabel

BookPublisher: Hoboken, NJ : John Wiley & Sons, [2007]Copyright date: ©2007Edition: Fourth edition.Description: xvi, 768 pages : illustrations ; 27 cm.Content type: text Media type: unmediated Carrier type: volumeISBN: 0471745898 (hardback); 9780471745891 (hardback).Subject(s): Statistics

| Probabilities

| Engineering -- Statistical methods

DDC classification: 519.502462

Contents:

The role of statistics in engineering -- Probability -- Discrete random variables and probability distributions -- Continuous random variables and probability distributions -- Joint probability distributions -- Random sampling and data description -- Sample distributions and point estimation of parameters -- Statistical intervals for a single sample -- Tests of hypothesis for a single sample --Statistical inference for two samples -- Simple linear regression and correlation -- Multiple linear regression -- Design and analysis of single-factor experiments: The analysis of variance -- Design of experiments with several factors -- Nonparametric statistics -- Statistical quality control.

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Enhanced descriptions from Syndetics:

With Montgomery and Runger's best-selling engineering statistics text, you can learn how to apply statistics to real engineering situations. The text shows you how to use statistical methods to design and develop new products, and new manufacturing systems and processes. You'll gain a better understanding of how these methods are used in everyday work, and get a taste of practical engineering experience through real-world, engineering-based examples and exercises.

Now revised, this Fourth Edition of Applied Statistics and Probability for Engineers features many new homework exercises, including a greater variation of problems and more computer problems.

Includes index.

CIT Module MATH7018 - Core reading.

CIT Module MATH7019 - Supplementary reading.

CIT Module MATH8005 - Core reading.

CIT Module MATH8008 - Supplementary reading.

CIT Module STAT7003 - Core reading.

CIT Module STAT8004 - Core reading.

CIT Module STAT8005 - Core reading.

CIT Module STAT6010 - Core reading.

Table of contents provided by Syndetics

Chapter 1 The Role of Statistics in Engineering (p. 1)
1-1 The Engineering Method and Statistical Thinking (p. 1)
1-2 Collecting Engineering Data (p. 4)
1-2.1 Basic Principles (p. 4)
1-2.2 Retrospective Study (p. 4)
1-2.3 Observational Study (p. 5)
1-2.4 Designed Experiments (p. 5)
1-2.5 Observing Processes Over Time (p. 8)
1-3 Mechanistic and Empirical Models (p. 11)
1-4 Probability and Probability Models (p. 14)
Chapter 2 Probability (p. 16)
2-1 Sample Spaces and Events (p. 17)
2-1.1 Random Experiments (p. 17)
2-1.2 Sample Spaces (p. 18)
2-1.3 Events (p. 22)
2-1.4 Counting Techniques (p. 24)
2-2 Interpretations of Probability (p. 31)
2-2.1 Introduction (p. 31)
2-2.2 Axioms of Probability (p. 34)
2-3 Addition Rules (p. 37)
2-4 Conditional Probability (p. 41)
2-5 Multiplication and Total Probability Rules (p. 46)
2-5.1 Multiplication Rule (p. 46)
2-5.2 Total Probability Rule (p. 47)
2-6 Independence (p. 50)
2-7 Bayes' Theorem (p. 55)
2-8 Random Variables (p. 58)
Chapter 3 Discrete Random Variables and Probability Distributions (p. 67)
3-1 Discrete Random Variables (p. 68)
3-2 Probability Distributions and Probability Mass Functions (p. 69)
3-3 Cumulative Distribution Functions (p. 72)
3-4 Mean and Variance of a Discrete Random Variable (p. 74)
3-5 Discrete Uniform Distribution (p. 78)
3-6 Binomial Distribution (p. 80)
3-7 Geometric and Negative Binomial Distributions (p. 87)
3-7.1 Geometric Distribution (p. 87)
3-7.2 Negative Binomial Distribution (p. 90)
3-8 Hypergeometric Distribution (p. 93)
3-9 Poisson Distribution (p. 99)
Chapter 4 Continuous Random Variables and Probability Distributions (p. 109)
4-1 Continuous Random Variables (p. 110)
4-2 Probability Distributions and Probability Density Functions (p. 110)
4-3 Cumulative Distribution Functions (p. 114)
4-4 Mean and Variance of a Continuous Random Variable (p. 117)
4-5 Continuous Uniform Distribution (p. 119)
4-6 Normal Distribution (p. 121)
4-7 Normal Approximation to the Binomial and Poisson Distributions (p. 131)
4-8 Exponential Distribution (p. 135)
4-9 Erlang and Gamma Distributions (p. 141)
4-10 Weibull Distribution (p. 145)
4-11 Lognormal Distribution (p. 147)
Chapter 5 Joint Probability Distributions (p. 153)
5-1 Two or More Discrete Random Variables (p. 154)
5-1.1 Joint Probability Distributions (p. 154)
5-1.2 Marginal Probability Distributions (p. 155)
5-1.3 Conditional Probability Distributions (p. 156)
5-1.4 Independence (p. 158)
5-1.5 Multiple Discrete Random Variables (p. 159)
5-1.6 Multinomial Probability Distribution (p. 162)
5-2 Two or More Continuous Random Variables (p. 166)
5-2.1 Joint Probability Distributions (p. 166)
5-2.2 Marginal Probability Distributions (p. 168)
5-2.3 Conditional Probability Distributions (p. 170)
5-2.4 Independence (p. 172)
5-2.5 Multiple Continuous Random Variables (p. 173)
5-3 Covariance and Correlation (p. 179)
5-4 Bivariate Normal Distribution (p. 184)
5-5 Linear Functions of Random Variables (p. 188)
5-6 Several Functions of Random Variables (p. 192)
Chpater 6 Random Sampling and Data Description (p. 198)
6-1 Numerical Summaries (p. 198)
6-2 Stem-and-Leaf Diagrams (p. 204)
6-3 Frequency Distributions and Histograms (p. 210)
6-4 Box Plots (p. 214)
6-5 Time Sequence Plots (p. 217)
6-6 Probability Plots (p. 221)
Chapter 7 Sampling Distributions and Point Estimation of Parameters (p. 229)
7-1 Introduction (p. 230)
7-2 Sampling Distributions and the Central Limit Theorem (p. 231)
7-3 General Concepts of Point Estimation (p. 237)
7-3.1 Unbiased Estimators (p. 237)
7-3.2 Variance of a Point Estimator (p. 239)
7-3.3 Standard Error: Reporting a Point Estimator (p. 239)
7-3.4 Mean Squared Error of an Estimator (p. 241)
7-4 Methods of Point Estimation (p. 243)
7-4.1 Method of Moments (p. 243)
7-4.2 Method of Maximum Likelihood (p. 245)
7-4.3 Bayesian Estimation of Parameters (p. 251)
Chapter 8 Statistical Intervals for a Single Sample (p. 258)
8-1 Introduction (p. 259)
8-2 Confidence Interval on the Mean of a Normal Distribution, Variance Known (p. 260)
8-2.1 Development of the Confidence Interval and Its Basic Properties (p. 260)
8-2.2 Choice of Sample Size (p. 263)
8-2.3 One-sided Confidence Bounds (p. 264)
8-2.4 General Method to Derive a Confidence Interval (p. 264)
8-2.5 Large-Sample Confidence Interval for [mu] (p. 265)
8-3 Confidence Interval on the Mean of a Normal Distribution, Variance Unknown (p. 268)
8-3.1 t Distribution (p. 269)
8-3.2 t Confidence Interval on [mu] (p. 270)
8-4 Confidence Interval on the Variance and Standard Deviation of a Normal Distribution (p. 273)
8-5 Large-Sample Confidence Interval for a Population Proportion (p. 277)
8-6 Guidelines for Constructing Confidence Intervals (p. 281)
8-7 Tolerance and Prediction Intervals (p. 281)
8-7.1 Prediction Interval for a Future Observation (p. 281)
8-7.2 Tolerance Interval for a Normal Distribution (p. 283)
Chapter 9 Tests of Hypotheses for a Single Sample (p. 290)
9-1 Hypothesis Testing (p. 291)
9-1.1 Statistical Hypotheses (p. 291)
9-1.2 Tests of statistical Hypotheses (p. 292)
9-1.3 One-Sided and Two-Sided Hypothesis (p. 298)
9-1.4 P-Values in Hypothesis Tests (p. 300)
9-1.5 Connection between Hypothesis Tests and Confidence Intervals (p. 301)
9-1.6 General Procedure for Hypothesis Tests (p. 301)
9-2 Tests on the Mean of a Normal Distribution, Variance Known (p. 305)
9-2.1 Hypothesis Tests on the Mean (p. 305)
9-2.2 Type II Error and Choice of Sample Size (p. 308)
9-2.3 Large Sample Test (p. 312)
9-3 Tests on the Mean of a Normal Distribution, Variance Unknown (p. 314)
9-3.1 Hypothesis Tests on the Mean (p. 314)
9-3.2 P-Value for a t-Test (p. 317)
9-3.3 Type II Error and Choice of Sample Size (p. 318)
9-4 Tests on the Variance and Standard Deviation of a Normal Distribution (p. 322)
9-4.1 Hypothesis Tests on the Variance (p. 322)
9-4.2 Type II Error and Choice of Sample Size (p. 324)
9-5 Tests on a Population Proportion (p. 325)
9-5.1 Large-Sample Tests on a Proportion (p. 326)
9-5.2 Type II Error and Choice of Sample Size (p. 328)
9-6 Summary Table of Inference Procedures for a Single Sample (p. 331)
9-7 Testing for Goodness of Fit (p. 331)
9-8 Contingency Table Tests (p. 335)
Chapter 10 Statistical Inference for Two Samples (p. 344)
10-1 Introduction (p. 345)
10-2 Inference on the Difference in Means of Two Normal Distributions, Variances Known (p. 346)
10-2.1 Hypothesis Tests on the Difference in Means, Variances Known (p. 347)
10-2.2 Type II Error and Choice of Sample Size (p. 348)
10-2.3 Confidence Interval on the Difference in Means, Variances Known (p. 350)
10-3 Inference on the Difference in Means of Two Normal Distributions, Variances Unknown (p. 354)
10-3.1 Hypothesis Tests on the Difference in Means, Variances Unknown (p. 354)
10-3.2 Type II Error and Choice of Sample Size (p. 360)
10-3.3 Confidence Interval on the Difference in Means, Variances Unknown (p. 361)
10-4 Paired t-Test (p. 366)
10-5 Inference on the Variances of Two Normal Distributions (p. 373)
10-5.1 F Distribution (p. 373)
10-5.2 Hypothesis Tests on the Ratio of Two Variances (p. 375)
10-5.3 Type II Error and Choice of Sample Size (p. 377)
10-5.4 Confidence Interval on the Ratio of Two Variances (p. 378)
10-6 Inference on Two Population Proportions (p. 379)
10-6.1 Large-Sample Tests on the Difference in Population Proportions (p. 380)
10-6.2 Type II Error and Choice of Sample Size (p. 382)
10-6.3 Confidence Interval on the Difference in Population Proportions (p. 383)
10-7 Summary Table and Roadmaps for Inference Procedures for Two Samples (p. 385)
Chapter 11 Simple Linear Regression and Correlation (p. 391)
11-1 Empirical Models (p. 392)
11-2 Simple Linear Regression (p. 395)
11-3 Properties of the Least Squares Estimators (p. 404)
11-4 Hypothesis Tests in Simple Linear Regression (p. 405)
11-4.1 Use of t-Tests (p. 405)
11-4.2 Analysis of Variance Approach to Test Significance of Regression (p. 407)
11-5 Confidence Intervals (p. 410)
11-5.1 Confidence Intervals on the Slope and Intercept (p. 410)
11-5.2 Confidence Interval on the Mean Response (p. 411)
11-6 Prediction of New Observations (p. 413)
11-7 Adequacy of the Regression Model (p. 416)
11-7.1 Residual Analysis (p. 416)
11-7.2 Coefficient of Determination (R[superscript 2]) (p. 418)
11-8 Correlation (p. 421)
11-9 Transformations (p. 427)
11-9.1 Logistic Regression available at www.wiley.com/college/montgomery
Chapter 12 Multiple Linear Regression (p. 435)
12-1 Multiple Linear Regression Model (p. 436)
12-1.1 Introduction (p. 436)
12-1.2 Least Squares Estimation of the Parameters (p. 439)
12-1.3 Matrix Approach to Multiple Linear Regression (p. 442)
12-1.4 Properties of the Least Squares Estimators (p. 447)
12-2 Hypothesis Tests in Multiple Linear Regression (p. 456)
12-2.1 Test for Significance of Regression (p. 456)
12-2.2 Tests on Individual Regression Coefficients and Subsets of Coefficients (p. 459)
12-3 Confidence Intervals in Multiple Linear Regression (p. 465)
12-3.1 Confidence Intervals on Individual Regression Coefficients (p. 465)
12-3.2 Confidence Interval on the Mean Response (p. 466)
12-4 Prediction of New Observations (p. 467)
12-5 Model Adequacy Checking (p. 470)
12-5.1 Residual Analysis (p. 470)
12-5.2 Influential Observations (p. 473)
12-6 Aspects of Multiple Regression Modeling (p. 476)
12-6.1 Polynomial Regression Models (p. 476)
12-6.2 Categorical Regressors and Indicator Variables (p. 478)
12-6.3 Selection of Variables and Model Building (p. 481)
12-6.4 Multicollinearity (p. 489)
Chapter 13 Design and Analysis of Single-Factor Experiments: The Analysis of Variance (p. 500)
13-1 Designing Engineering Experiments (p. 501)
13-2 Completely Randomized Single-Factor Experiment (p. 502)
13-2.1 Example: Tensile Strength (p. 502)
13-2.2 Analysis of Variance (p. 503)
13-2.3 Multiple Comparisons Following the ANOVA (p. 511)
13-2.4 Residual Analysis and Model Checking (p. 514)
13-2.5 Determining Sample Size (p. 514)
13-3 Random Effects Model (p. 521)
13-3.1 Fixed Versus Random Factors (p. 521)
13-3.2 ANOVA and Variance Components (p. 521)
13-4 Randomized Complete Block Design (p. 525)
13-4.1 Design and Statistical Analysis (p. 525)
13-4.2 Multiple Comparisons (p. 530)
13-4.3 Residual Analysis and Model Checking (p. 531)
Chapter 14 Design of Experiments with Several Factors (p. 538)
14-1 Introduction (p. 539)
14-2 Factorial Experiments (p. 541)
14-3 Two-Factor Factorial Experiments (p. 545)
14-3.1 Statistical Analysis of the Fixed-Effects Model (p. 546)
14-3.2 Model Adequacy Checking (p. 552)
14-3.3 One Observation Per Cell (p. 552)
14-4 General Factorial Experiments (p. 555)
14-5 2[superscript k] Factorial Designs (p. 558)
14-5.1 2[superscript 2] Design (p. 559)
14-5.2 2[superscript k] Design for k [greater than or equal] 3 Factors (p. 564)
14-5.3 Single Replicate of the 2[superscript k] Design (p. 572)
14-5.4 Addition of Center Points to a 2[superscript k] Design (p. 576)
14-6 Blocking and Confounding in the 2[superscript k] Design (p. 581)
14-7 Fractional Replication of the 2[superscript k] Design (p. 587)
14-7.1 One Half Fraction of the 2[superscript k] Design (p. 587)
14-7.2 Smaller Fractions: The 2[superscript k-p] Fractional Factorial (p. 594)
14-8 Response Surface Methods and Designs (p. 602)
Chapter 15 Nonparametric Statistics (p. 618)
15-1 Introduction (p. 619)
15-2 Sign Test (p. 619)
15-2.1 Description of the Test (p. 619)
15-2.2 Sign Test for Paired Samples (p. 623)
15-2.3 Type II Error for the Sign Test (p. 624)
15-2.4 Comparison to the t-Test (p. 626)
15-3 Wilcoxon Signed-Rank Test (p. 628)
15-3.1 Description of the Test (p. 628)
15-3.2 Large-Sample Approximation (p. 630)
15-3.3 Paired Observations (p. 630)
15-3.4 Comparison to the t-Test (p. 631)
15-4 Wilcoxon Rank-Sum Test (p. 632)
15-4.1 Description of the Test (p. 632)
15-4.2 Large-Sample Approximation (p. 634)
15-4.3 Comparison to the t-Test (p. 635)
15-5 Nonparametric Methods in the Analysis of Variance (p. 636)
15-5.1 Kruskal-Wallis Test (p. 636)
15-5.2 Rank Transformation (p. 638)
15-6 Runs Test (p. 639)
Chapter 16 Statistical Quality Control (p. 644)
16-1 Quality Improvement and Statistics (p. 645)
16-2 Statistical Quality Control (p. 646)
16-3 Statistical Process Control (p. 646)
16-4 Introduction to Control Charts (p. 647)
16-4.1 Basic Principles (p. 647)
16-4.2 Design of a Control Chart (p. 651)
16-4.3 Rational Subgroups (p. 652)
16-4.4 Analysis of Patterns on Control Charts (p. 653)
16-5 X and R or S Control Charts (p. 656)
16-6 Control Charts for Individual Measurements (p. 664)
16-7 Process Capability (p. 669)
16-8 Attribute Control Charts (p. 674)
16-8.1 P Chart (Control Chart for Proportion) (p. 674)
16-8.2 U Chart (Control Chart for Defects per Unit) (p. 676)
16-9 Control Chart Performance (p. 679)
16-10 Time-Weighted Charts (p. 681)
16-10.1 Cumulative Sum Control Chart (p. 681)
16-10.2 Exponentially Weighted Moving Average Control Chart (p. 687)
16-11 Other SPC Problem-Solving Tools (p. 693)
16-12 Implementing SPC (p. 695)
Appendices (p. 706)
Appendix A Statistical Tables and Charts (p. 707)
Table I Summary of Common Probability Distributions (p. 708)
Table II Cumulative Binomial Distribution (p. 709)
Table III Cumulative Standard Normal Distribution (p. 712)
Table IV Percentage Points [characters not reproducible] of the Chi-Squared Distribution (p. 714)
Table V Percentage Points t[subscript alpha, upsilon] of the t-distribution (p. 715)
Table VI Percentage Points [characters not reproducible] of the F-distribution (p. 716)
Chart VII Operating Characteristic Curves (p. 721)
Table VIII Critical Values for the Sign Test (p. 730)
Table IX Critical Values for the Wilcoxon Signed-Rank Test (p. 730)
Table X Critical Values for the Wilcoxon Rank-Sum Test (p. 731)
Table XI Factors for Constructing Variables Control Charts (p. 732)
Table XII Factors for Tolerance Intervals (p. 733)
Appendix B Answers to Selected Exercises (p. 735)
Appendix C Bibliography available at www.wiley.com/college/montgomery
Glossary (p. 751)
Index (p. 762)
Applications in Examples and Exercises Continued (p. 766)