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Probability and Statistics for Engineers and Scientists,9780534386696
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Probability and Statistics for Engineers and Scientists

by
Edition:
2nd
ISBN13:

9780534386696

ISBN10:
0534386695
Format:
Hardcover
Pub. Date:
12/5/2001
Publisher(s):
Duxbury Press

Questions About This Book?

What version or edition is this?
This is the 2nd edition with a publication date of 12/5/2001.
What is included with this book?
  • The New copy of this book will include any supplemental materials advertised. Please check the title of the book to determine if it should include any CDs, lab manuals, study guides, etc.

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Summary

1. PROBABILITY THEORY Probabilities. Events. Combinations of Events. Conditional Probability. Probabilities of Event Intersections. Posterior Probabilities. Counting Techniques. 2. RANDOM VARIABLES Discrete Random Variables. Continuous Random Variables. The Expectation of a Random Variable. The Variance of a Random Variable. Jointly Distributed Random Variables. Combinations and Functions of Random Variables. 3. DISCRETE PROBABILITY DISTRIBUTIONS The Binomial Distribution. The Geometric and Negative Binomial Distributions. The Hypergeometric Distribution. The Poisson Distribution. The Multinomial Distribution. 4. CONTINUOUS PROBABILITY DISTRIBUTIONS The Uniform Distribution. The Exponential Distribution. The Gamma Distribution. The Weibull Distribution. The Beta Distribution. 5. THE NORMAL DISTRIBUTION Probability Calculations Using the Normal Distribution. Linear Combinations of Normal Random Variables. Approximating Distributions with the Normal Distribution. Distributions Related to the Normal Distribution. 6. DESCRIPTIVE STATISTICS Experimentation. Data Presentation. Sample Statistics. Examples. 7. STATISTICAL ESTIMATION AND SAMPLING DISTRIBUTIONS Point Estimates. Properties of Point Estimates. Sampling Distributions. Constructing Parameter Estimates. 8. INFERENCES ON A POPULATION MEAN Confidence Intervals. Hypothesis Testing. Summary. 9. COMPARING TWO POPULATION MEANS Introduction. Analysis of Paired Samples. Analysis of Independent Samples. Summary. 10. DISCRETE DATA ANALYSIS Inferences on a population Proportion. Comparing Two Population Proportions. Goodness-of-Fit Tests for One-Way Contingency Tables. Testing for Independence in Two-Way Contingency Tables. 11. THE ANALYSIS OF VARIANCE One Factor Analysis of Variance. Randomized Block Designs. 12. SIMPLE LINEAR REGRESSION AND CORRELATION The Simple Linear Regression Model. Fitting the Regression Line. Inferences on the Slope Parameter 1. Inferences on the Regression Line. Prediction Intervals for Future Response Values. The Analysis of Variance Tables. Residual Analysis. Variable Transformation. Correlation Analysis. 13. MULTIPLE LINEAR REGRESSION AND NONLINEAR REGRESSION Introduction to Multiple Linear Regression. Examples of Multiple Linear Regression. matrix Algebra Formulation of Multi-le Linear Regression. Evaluating Model Adequacy. Nonlinear Regression. 14. MULTIFACTOR EXPERIMENTAL DESIGN AND ANALYSIS Experiments with Two Factors. Experiments with Three or More Factors. 15. NONPARAMETRIC STATISTICAL ANALYSIS The analysis of a single Population. Comparing Two Populations. Comparing Three or More Populations. 16. QUALITY CONTROL METHODS Introduction. Statistical Process control. Variable Control Charts. Attribute Control Charts. Acceptance Sampling. 17. RELIABILITY ANALYSIS AND LIFE TESTING System Reliability. Modeling Failure Rates. Life Testing. TABLES. ANSWERS TO ODD-NUMBERED PROBLEMS. INDEX.

Table of Contents

Preface ix
Probability Theory
1(72)
Probabilities
1(8)
Events
9(7)
Combinations of Events
16(21)
Conditional Probability
37(7)
Probabilities of Event Intersections
44(11)
Posterior Probabilities
55(6)
Counting Techniques
61(9)
Supplementary Problems
70(3)
Random Variables
73(83)
Discrete Random Variables
73(12)
Continuous Random Variables
85(13)
The Expectation of a Random Variables
98(12)
The Variance of a Random Variables
110(13)
Jointly Distributed Random Variables
123(18)
Combinations and Functions of Random Variables
141(12)
Supplementary Problems
153(3)
Discrete Probability Distributions
156(43)
The Binomial Distribution
156(15)
The Geometric and Negative Binomial Distributions
171(9)
The Hypergeometric Distribution
180(5)
The Poisson Distribution
185(8)
The Multinomial Distribution
193(5)
Supplementary Problems
198(1)
Continuous Probability Distributions
199(33)
The Uniform Distribution
199(4)
The Exponential Distribution
203(10)
The Gamma Distribution
213(6)
The Weibull Distribution
219(6)
The Beta Distribution
225(4)
Supplementary Problems
229(3)
The Normal Distribution
232(54)
Probability Calculations Using the Normal Distribution
232(16)
Linear Combinations of Normal Random Variables
248(11)
Approximating Distributions with the Normal Distribution
259(12)
Distributions Related to the Normal Distribution
271(13)
Supplementary Problems
284(2)
Descriptive Statistics
286(35)
Experimentation
286(8)
Data Presentation
294(12)
Sample Statistics
306(8)
Example
314(4)
Supplementary Problems
318(3)
Statistical Estimation and Sampling Distributions
321(36)
Point Estimates
321(5)
Properties of Point Estimates
326(12)
Sampling Distributions
338(9)
Constructing Parameter Estimates
347(8)
Supplementary Problems
355(2)
Inferences on a Population Mean
357(60)
Confidence Intervals
357(18)
Hypothesis Testing
375(37)
Summary
412(2)
Supplementary Problems
414(3)
Comparing Two Population Means
417(48)
Introduction
417(8)
Analysis of Paired Samples
425(7)
Analysis of Independent Samples
432(25)
Summary
457(4)
Supplementary Problems
461(4)
Discrete Data Analysis
465(70)
Inferences on a Population Proportion
465(26)
Comparing Two Population Proportions
491(12)
Goodness of Fit Tests for One-Way Contingency Tables
503(16)
Testing for Independence in Two-Way Contingency Tables
519(13)
Supplementary Problems
532(3)
The Analysis of Variance
535(59)
One Factor Analysis of Variance
535(31)
Randomized Block Designs
566(24)
Supplementary Problems
590(4)
Simple Linear Regression and Correlation
594(74)
The Simple Linear Regression Model
594(10)
Fitting the Regression Line
604(14)
Inferences on the Slope Parameter β1
618(9)
Inferences on the Regression Line
627(6)
Prediction Intervals for Future Response Values
633(6)
The Analysis of Variance Table
639(6)
Residual Analysis
645(5)
Variable Transformations
650(7)
Correlation Analysis
657(6)
Supplementary Problems
663(5)
Multiple Linear Regression and Nonlinear Regression
668(54)
Introduction to Multiple Linear Regression
668(11)
Examples of Multiple Linear Regression
679(18)
Matrix Algebra Formulation of Multiple Linear Regression
697(11)
Evaluating Model Adequacy
708(7)
Nonlinear Regression
715(4)
Supplementary Problems
719(3)
Multifactor Experimental Design and Analysis
722(56)
Experiments with Two Factors
722(37)
Experiments with Three or More Factors
759(14)
Supplementary Problems
773(5)
Nonparametric Statistical Analysis
778(49)
The Analysis of a Single Population
779(26)
Comparing Two Populations
805(11)
Comparing Three or More Populations
816(8)
Supplementary Problems
824(3)
Quality Control Methods
827(32)
Introduction
827(1)
Statistical Process Control
827(8)
Variable Control Charts
835(9)
Attribute Control Charts
844(7)
Acceptance Sampling
851(6)
Supplementary Problems
857(2)
Reliability Analysis and Life Testing
859(22)
System Reliability
859(6)
Modeling Failure Rates
865(5)
Life Testing
870(9)
Supplementary Problems
879(2)
Tables 881(10)
Cumulative Distribution Function of the Standard Normal Distribution
881(2)
Critical Points of the Chi-Square Distribution
883(1)
Critical Points of the t-Distribution
884(1)
Critical Points of the F-Distribution
885(3)
Critical Points qα,k,v of the Studentized Range Distribution
888(2)
Critical Points dα,n for Kolmogorov and Kolmogorov-Smirnov Procedures
890(1)
Answers to Odd-Numbered Problems 891(18)
Index 909


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