05391nam 22006733u 450 991083038290332120230721030243.01-281-09412-997866110941260-470-12844-50-470-12843-7(CKB)1000000000377260(EBL)319281(SSID)ssj0000204320(PQKBManifestationID)11199469(PQKBTitleCode)TC0000204320(PQKBWorkID)10187959(PQKB)11053039(MiAaPQ)EBC319281(OCoLC)181345645(EXLCZ)99100000000037726020131014d2007|||| u|| |engur|n|---|||||txtccrModern Engineering Statistics[electronic resource]Hoboken Wiley20071 online resource (608 p.)Description based upon print version of record.0-470-08187-2 Modern Engineering Statistics; Contents; Preface; 1. Methods of Collecting and Presenting Data; 1.1 Observational Data and Data from Designed Experiments; 1.2 Populations and Samples; 1.3 Variables; 1.4 Methods of Displaying Small Data Sets; 1.4.1 Stem-and-Leaf Display; 1.4.2 Time Sequence Plot and Control Chart; 1.4.3 Lag Plot; 1.4.4 Scatter Plot; 1.4.5 Digidot Plot; 1.4.6 Dotplot; 1.5 Methods of Displaying Large Data Sets; 1.5.1 Histogram; 1.5.2 Boxplot; 1.6 Outliers; 1.7 Other Methods; 1.8 Extremely Large Data Sets: Data Mining; 1.9 Graphical Methods: Recommendations; 1.10 SummaryReferencesExercises; 2. Measures of Location and Dispersion; 2.1 Estimating Location Parameters; 2.2 Estimating Dispersion Parameters; 2.3 Estimating Parameters from Grouped Data; 2.4 Estimates from a Boxplot; 2.5 Computing Sample Statistics with MINITAB; 2.6 Summary; Reference; Exercises; 3. Probability and Common Probability Distributions; 3.1 Probability: From the Ethereal to the Concrete; 3.1.1 Manufacturing Applications; 3.2 Probability Concepts and Rules; 3.2.1 Extension to Multiple Events; 3.2.1.1 Law of Total Probability and Bayes' Theorem; 3.3 Common Discrete Distributions3.3.1 Expected Value and Variance3.3.2 Binomial Distribution; 3.3.2.1 Testing for the Appropriateness of the Binomial Model; 3.3.3 Hypergeometric Distribution; 3.3.4 Poisson Distribution; 3.3.4.1 Testing for the Appropriateness of the Poisson Model; 3.3.5 Geometric Distribution; 3.4 Common Continuous Distributions; 3.4.1 Expected Value and Variance; 3.4.2 Determining Probabilities for Continuous Random Variables; 3.4.3 Normal Distribution; 3.4.3.1 Software-Aided Normal Probability Computations; 3.4.3.2 Testing the Normality Assumption; 3.4.4 t-Distribution; 3.4.5 Gamma Distribution3.4.5.1 Chi-Square Distribution3.4.5.2 Exponential Distribution; 3.4.6 Weibull Distribution; 3.4.7 Smallest Extreme Value Distribution; 3.4.8 Lognormal Distribution; 3.4.9 F Distribution; 3.5 General Distribution Fitting; 3.6 How to Select a Distribution; 3.7 Summary; References; Exercises; 4. Point Estimation; 4.1 Point Estimators and Point Estimates; 4.2 Desirable Properties of Point Estimators; 4.2.1 Unbiasedness and Consistency; 4.2.2 Minimum Variance; 4.2.3 Estimators Whose Properties Depend on the Assumed Distribution; 4.2.4 Comparing Biased and Unbiased Estimators4.3 Distributions of Sampling Statistics4.3.1 Central Limit Theorem; 4.3.1.1 Illustration of Central Limit Theorem; 4.3.2 Statistics with Nonnormal Sampling Distributions; 4.4 Methods of Obtaining Estimators; 4.4.1 Method of Maximum Likelihood; 4.4.2 Method of Moments; 4.4.3 Method of Least Squares; 4.5 Estimating σ; 4.6 Estimating Parameters Without Data; 4.7 Summary; References; Exercises; 5. Confidence Intervals and Hypothesis Tests-One Sample; 5.1 Confidence Interval for μ: Normal Distribution, σ Not Estimated from Sample Data; 5.1.1 Sample Size Determination; 5.1.2 Interpretation and Use5.1.3 General Form of Confidence IntervalsAn introductory perspective on statistical applications in the field of engineering Modern Engineering Statistics presents state-of-the-art statistical methodology germane to engineering applications. With a nice blend of methodology and applications, this book provides and carefully explains the concepts necessary for students to fully grasp and appreciate contemporary statistical techniques in the context of engineering. With almost thirty years of teaching experience, many of which were spent teaching engineering statistics courses, the author has successfully developed a Engineering - Statistical methodsEngineeringEngineeringStatistical methodsEngineering & Applied SciencesHILCCApplied MathematicsHILCCEngineering - Statistical methods.Engineering.EngineeringStatistical methodsEngineering & Applied SciencesApplied Mathematics519.5620.0072Ryan Thomas P117276AU-PeELAU-PeELAU-PeELBOOK9910830382903321Modern engineering statistics1071327UNINA