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Probability and Statistics for Engineers and Scientists,9780131877115
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Probability and Statistics for Engineers and Scientists

by ; ; ;
Edition:
8th
ISBN13:

9780131877115

ISBN10:
0131877119
Format:
Hardcover
Pub. Date:
1/1/2007
Publisher(s):
Prentice Hall
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Summary

With its unique balance of theory and methodology, this classic text provides a rigorous introduction to basic probability theory and statistical inference, motivated by interesting, relevant applications.Offers extensively updated coverage, new problem sets, and chapter-ending material to enhance the bookrs"s relevance to todayrs"s engineers and scientists. Includes new problem sets demonstrating updated applications to engineering as well as biological, physical, and computer science. Emphasizes key ideas as well as the risks and hazards associated with practical application of the material. Includes new material on topics including: difference between discrete and continuous measurements; binary data; quartiles; importance of experimental design; "dummy" variables; rules for expectations and variances of linear functions; Poisson distribution; Weibull and lognormal distributions; central limit theorem, and data plotting. Introduces Bayesian statistics, including its applications to many fields. For those interested in learning more about probability and statistics.

Table of Contents

Preface xv
Introduction to Statistics and Data Analysis
1(30)
Overview: Statistical Inference, Samples, Populations and Experimental Design
1(3)
The Role of Probability
4(3)
Sampling Procedures; Collection of Data
7(4)
Measures of Location: The Sample Mean and Median
11(3)
Exercises
13(1)
Measures of Variability
14(3)
Exercises
17(1)
Discrete and Continuous Data
17(2)
Statistical Modeling, Scientific Inspection, and Graphical Diaganostics
19(1)
Graphical Methods and Data Description
20(5)
General Types of Statistical Studies: Designed Experiment, Observational Study, and Retrospective Study
25(6)
Exercises
28(3)
Probability
31(46)
Sample Space
31(3)
Events
34(6)
Exercises
38(2)
Counting Sample Points
40(8)
Exercises
47(1)
Probability of an Event
48(4)
Additive Rules
52(6)
Exercises
55(3)
Conditional Probability
58(3)
Multiplicative Rules
61(7)
Exercises
65(3)
Bayes' Rule
68(9)
Exercises
72(1)
Review Exercises
73(4)
Random Variables and Probability Distributions
77(30)
Concept of a Random Variable
77(3)
Discrete Probability Distributions
80(4)
Continuous Probability Distributions
84(7)
Exercises
88(3)
Joint Probability Distributions
91(15)
Exercises
101(2)
Review Exercises
103(3)
Potential Misconceptions and Hazards; Relationship to Material in Other Chapters
106(1)
Mathematical Expectation
107(34)
Mean of a Random Variable
107(8)
Exercises
113(2)
Variance and Covariance of Random Variables
115(8)
Exercises
122(1)
Means and Variances of Linear Combinations of Random Variables
123(8)
Chebyshev's Theorem
131(7)
Exercises
134(2)
Review Exercises
136(2)
Potential Misconceptions and Hazards; Relationship to Material in Other Chapters
138(3)
Some Discrete Probability Distributions
141(30)
Introduction and Motivation
141(1)
Discrete Uniform Distribution
141(2)
Binomial and Multinomial Distributions
143(9)
Exercises
150(2)
Hypergeometric Distribution
152(6)
Exercises
157(1)
Negative Binomial and Geometric: Distributions
158(3)
Poisson Distribution and the Poisson Process
161(8)
Exercises
165(2)
Review Exercises
167(2)
Potential Misconceptions and Hazards; Relationship to Material in Other Chapters
169(2)
Some Continuous Probability Distributions
171(40)
Continuous Uniform Distribution
171(1)
Normal Distribution
172(4)
Areas under the Normal Curve
176(6)
Applications of the Normal Distribution
182(5)
Exercises
185(2)
Normal Approximation to the Binomial
187(7)
Exercises
193(1)
Gamma and Exponential Distributions
194(3)
Applications of the Exponential and Gamma Distributions
197(3)
Chi-Squared Distribution
200(1)
Lognormal Distribution
201(1)
Weibull Distribution (Optional)
202(7)
Exercises
205(1)
Review Exercises
206(3)
Potential Misconceptions and Hazards; Relationship to Material in Other Chapters
209(2)
Functions of Random Variables (Optional)
211(18)
Introduction
211(1)
Transformations of Variables
211(8)
Moments and Moment-Generating Functions
219(10)
Exercises
226(3)
Fundamental Sampling Distributions and Data Descriptions
229(40)
Random Sampling
229(2)
Some Important Statistics
231(5)
Exercises
234(2)
Data Displays and Graphical Methods
236(7)
Sampling Distributions
243(1)
Sampling Distribution of Means
244(10)
Exercises
251(3)
Sampling Distribution of S2
254(3)
t-Distribution
257(4)
F-Distribution
261(7)
Exercises
265(1)
Review Exercises
266(2)
Potential Misconceptions and Hazards; Relationship to Material in Other Chapters
268(1)
One- and Two-Sample Estimation Problems
269(52)
Introduction
269(1)
Statistical Inference
269(1)
Classical Methods of Estimation
270(4)
Single Sample: Estimating the Mean
274(6)
Standard Error of a Point Estimate
280(1)
Prediction Intervals
281(2)
Tolerance Limits
283(5)
Exercises
285(3)
Two Samples: Estimating the Difference between Two Means
288(6)
Paired Observations
294(5)
Exercises
297(2)
Single Sample: Estimating a Proportion
299(3)
Two Samples: Estimating the Difference between Two Proportions
302(4)
Exercises
304(2)
Single Sample: Estimating the Variance
306(2)
Two Samples: Estimating the Ratio of Two Variances
308(2)
Exercises
310(1)
Maximum Likelihood Estimation (Optional)
310(9)
Exercises
315(1)
Review Exercises
315(4)
Potential Misconceptions and Hazards: Relationship to Material in Other Chapters
319(2)
One- and Two-Sample Tests of Hypotheses
321(68)
Statistical Hypotheses: General Concepts
321(2)
Testing a Statistical Hypothesis
323(9)
One- and Two-Tailed Tests
332(2)
The Use of P-Values for Decision Making in Testing Hypotheses
334(4)
Exercises
336(2)
Single Sample: Tests Concerning a Single Mean (Variance Known)
338(3)
Relationship to Confidence Interval Estimation
341(1)
Single Sample: Tests on a Single Mean (Variance Unknown)
342(3)
Two Samples: Tests on Two Means
345(5)
Choice of Sample Size for Testing Means
350(5)
Graphical Methods for Comparing Means
355(6)
Exercises
357(4)
One Sample: Test on a Single Proportion
361(3)
Two Samples: Tests on Two Proportions
364(3)
Exercises
366(1)
One- and Two-Sample Tests Concerning Variances
367(4)
Exercises
370(1)
Goodness-of-Fit Test
371(3)
Test for Independence (Categorical Data)
374(3)
Test for Homogeneity
377(1)
Testing for Several Proportions
378(2)
Two-Sample Case Study
380(7)
Exercises
383(2)
Review Exercises
385(2)
Potential Misconceptions and Hazards; Relationship to Material in Other Chapters
387(2)
Simple Linear Regression and Correlation
389(56)
Introduction to Linear Regression
389(1)
The Simple Linear Regression Model
390(4)
Least Squares and the Fitted Model
394(6)
Exercises
397(3)
Properties of the Least Squares Estimators
400(2)
Inferences Concerning the Regression Coefficients
402(7)
Prediction
409(5)
Exercises
412(2)
Choice of a Regression Model
414(1)
Analysis-of-Variance Approach
415(2)
Test for Linearity of Regression: Data with Repeated Observations
417(8)
Exercises
423(2)
Data Plots and Transformations
425(5)
Simple Linear Regression Case Study
430(2)
Correlation
432(11)
Exercises
438(1)
Review Exercises
438(5)
Potential Misconceptions and Hazards; Relationship to Material in Other Chapters
443(2)
Multiple Linear Regression and Certain Nonlinear Regression Models
445(66)
Introduction
445(1)
Estimating the Coefficients
446(3)
Linear Regression Model Using Matrices (Optional)
449(7)
Exercises
452(4)
Properties of the Least Squares Estimators
456(2)
Inferences in Multiple Linear Regression
458(7)
Exercises
464(1)
Choice of a Fitted Model through Hypothesis Testing
465(4)
Special Case of Orthogonality (Optional)
469(5)
Exercises
473(1)
Categorical or Indicator Variables
474(5)
Exercises
478(1)
Sequential Methods for Model Selection
479(6)
Study of Residuals and Violation of Assumptions
485(5)
Cross Validation, Cp, and Other Criteria for Model Selection
490(9)
Exercises
496(3)
Special Nonlinear Models for Nonideal Conditions
499(9)
Review Exercises
503(5)
Potential Misconceptions and Hazards; Relationship to Material in Other Chapters
508(3)
One-Factor Experiments: General
511(62)
Analysis-of-Variance Technique
511(1)
The Strategy of Experimental Design
512(1)
One-Way Analysis of Variance: Completely Randomized Design (One-Way ANOVA)
513(5)
Tests for the Equality of Several Variances
518(5)
Exercises
521(2)
Single-Degree-of-Freedom Comparisons
523(4)
Multiple Comparisons
527(4)
Comparing Treatments with a Control
531(4)
Exercises
533(2)
Comparing a Set of Treatments in Blocks
535(2)
Randomized Complete Block Designs
537(7)
Graphical Methods and Model Checking
544(3)
Data Transformations In Analysis of Variance)
547(2)
Latin Squares (Optional)
549(6)
Exercises
551(4)
Random Effects Models
555(4)
Power of Analysis-of-Variance Tests
559(4)
Case Study
563(8)
Exercises
565(2)
Review Exercises
567(4)
Potential Misconceptions and Hazards; Relationship to Material in Other Chapters
571(2)
Factorial Experiments (Two or More Factors)
573(38)
Introduction
573(1)
Interaction in the Two-Factor Experiment
574(3)
Two-Factor Analysis of Variance
577(13)
Exercises
587(3)
Three-Factor Experiments
590(10)
Exercises
597(3)
Model II and III Factorial Experiments
600(3)
Choice of Sample Size
603(6)
Exercises
605(2)
Review Exercises
607(2)
Potential Misconceptions and Hazards; Relationship to Material in Other Chapters
609(2)
2k Factorial Experiments and Fractions
611(60)
Introduction
611(1)
The 2k Factorial: Calculation of Effects and Analysis of Variance
612(6)
Nonreplicated 2k Factorial Experiment
618(1)
Injection Molding Case Study
619(6)
Exercises
622(3)
Factorial Experiments in a Regression Setting
625(6)
The Orthogonal Design
631(8)
Factorial Experiments in Incomplete Blocks
639(8)
Exercises
645(2)
Fractional Factorial Experiments
647(6)
Analysis of Fractional Factorial Experiments
653(4)
Exercises
656(1)
Higher Fractions and Screening Designs
657(1)
Construction of Resolution III and IV Designs
658(2)
Other Two-Level Resolution III Designs: The Plackett-Burman Designs
660(1)
Robust Parameter Design
661(8)
Exercises
666(1)
Review Exercises
667(2)
Potential Misconceptions and Hazards: Relationship to Material in Other Chapters
669(2)
Nonparametric Statistics
671(26)
Nonparametric Tests
671(5)
Signed-Rank Test
676(5)
Exercises
679(2)
Wilcoxon Rank-Sum Test
681(3)
Kruskal-Wallis Test
684(3)
Exercises
686(1)
Runs Test
687(3)
Tolerance Limits
690(1)
Rank Correlation Coefficient
690(7)
Exercises
693(2)
Review Exercises
695(2)
Statistical Quality Control
697(28)
Introduction
697(2)
Nature of the Control Limits
699(1)
Purposes of the Control Chart
699(1)
Control Charts for Variables
700(13)
Control Charts for Attributes
713(8)
Cusum Control Charts
721(4)
Review Exercises
722(3)
Bayesian Statistics (Optional)
725(12)
Bayesian Concepts
725(1)
Bayesian Inferences
726(6)
Bayes Estimates Using Decision Theory Framework
732(5)
Exercises
734(3)
Bibliography 737(4)
A. Statistical Tables and Proofs 741(54)
B. Answers to Odd-Numbered Non-Review Exercises 795(16)
Index 811


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