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Statistics for Engineering and the Sciences,9780023805813
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Statistics for Engineering and the Sciences

by ;
ISBN13:

9780023805813

ISBN10:
0023805811
Format:
Hardcover
Pub. Date:
1/1/1995
Publisher(s):
Prentice Hall

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Summary

This book illustrates basic statistical concepts with extensive applications in engineering and scientific contexts. The book includes optional theoretical exercises, allowing readers who choose to emphasize theory to do so with requiring additional materials. The fourth edition contains SAS and MINITAB computer printout results for all analyses performedplus new exercises based on magazine and journal articles and news reports.KEY TOPICS:A section on "Detecting Normal Distributions" (Chapter 5) gives readers insights on when it is reasonable to assume that underlying data is normally distributed. There is a comprehensive example on model building (Chapter 13) and emphasis on the regression approach to a Nova (also presents the traditional approach). There are two sections discussing principles of experimental design, i.e., noise-reducing and volume-increasing design, a section on "Total Quality Management" and coverage of statistical computing. There are optional, calculus-based theoretical exercises, and real data sets, extracted from scientific studies, are provided in an appendix. Numerical answers to all applied exercises are included in an appendixgiving readers immediate feedback on their work.

Table of Contents

Preface xiii
Introduction
1(14)
Statistics: The Science of Data
2(3)
Types of Data
5(2)
The Role of Statistics
7(1)
Summary
8(7)
Entering and Listing Data
10(3)
Accessing an External Data File (Optional)
13(2)
Descriptive Statistics
15(62)
Graphical and Numerical Methods for Describing Qualitative Data
16(9)
Graphical Methods for Describing Quantitative Data
25(14)
Numerical Methods for Describing Quantitative Data
39(1)
Measures of Central Tendency
39(5)
Measures of Variation
44(9)
Measures of Relative Standing
53(4)
Methods for Detecting Outliers
57(5)
Summary
62(15)
Graphical and Numerical Data Description
70(7)
Probability
77(66)
The Role of Probability in Statistics
78(1)
Events, Sample Spaces, and Probability
78(13)
Compound Events
91(3)
Complementary Events
94(4)
Conditional Probability
98(5)
Probability Rules for Unions and Intersections
103(13)
Bayes' Rule (Optional)
116(3)
Some Counting Rules
119(14)
Probability and Statistics: An Example
133(3)
Summary
136(7)
Discrete Random Variables
143(60)
Discrete Random Variables
144(1)
The Probability Distribution for a Discrete Random Variable
145(5)
The Expected Value for a Random Variable y or for a Function g(y) of y
150(5)
Some Useful Expectation Theorems
155(2)
Bernoulli Trials
157(2)
The Binomial Probability Distribution
159(8)
The Multinomial Probability Distribution
167(7)
The Negative Binomial and the Geometric Probability Distributions
174(4)
The Hypergeometric Probability Distribution
178(6)
The Poisson Probability Distribution
184(8)
Moments and Moment Generating Functions (Optional)
192(5)
Summary
197(6)
Continuous Random Variables
203(54)
Continuous Random Variables
204(2)
The Density Function for a Continuous Random Variable
206(5)
Expected Values for Continuous Random Variables
211(6)
The Uniform Probability Distribution
217(4)
The Normal Probability Distribution
221(7)
Descriptive Methods for Assessing Normality
228(7)
Gamma-Type Probability Distributions
235(6)
The Weibull Probability Distribution
241(3)
Beta-Type Probability Distributions
244(5)
Moments and Moment Generating Functions (Optional)
249(2)
Summary
251(6)
Bivariate Probability Distributions
257(32)
Bivariate Probability Distributions for Discrete Random Variables
258(7)
Bivariate Probability Distributions for Continuous Random Variables
265(6)
The Expected Value of Functions of Two Random Variables
271(2)
Independence
273(3)
The Covariance of Two Random Variables
276(3)
The Correlation Coefficient p
279(2)
The Expected Value and Variance of Linear Functions of Random Variables (Optional)
281(4)
Summary
285(4)
Sampling Distributions
289(48)
Random Sampling
290(4)
Sampling Distributions
294(1)
Probability Distributions of Functions of Random Variables (Optional)
295(7)
Approximating a Sampling Distribution by Simulation
302(8)
The Sampling Distributions of Means and Sums
310(8)
Normal Approximation to the Binomial Distribution
318(4)
Sampling Distributions Related to the Normal Distribution
322(6)
Summary
328(9)
Generating Random Samples
332(5)
Estimation
337(84)
Estimators
338(1)
Properties of Point Estimators
339(5)
Finding Point Estimators: Methods of Estimation
344(8)
Finding Interval Estimators: The Pivotal Method
352(12)
Estimation of a Population Mean
364(7)
Estimation of the Difference Between Two Population Means: Independent Samples
371(10)
Estimation of the Difference Between Two Population Means: Matched Pairs
381(6)
Estimation of a Population Proportion
387(3)
Estimation of the Difference Between Two Population Proportions
390(4)
Estimation of a Population Variance
394(5)
Estimation of the Ratio of Two Population Variances
399(6)
Choosing the Sample Size
405(5)
Summary
410(11)
Confidence Intervals for Means
417(4)
Tests of Hypotheses
421(74)
The Relationship Between Statistical Tests of Hypotheses and Confidence Intervals
422(1)
Elements of a Statistical Test
423(1)
Evaluation the Properties of a Statistical Test
424(6)
Finding Statistical Tests: An Example of a Large-Sample Test
430(6)
Choosing the Null and Alternative Hypotheses
436(2)
Testing a Population Mean
438(7)
The Observed Significance Level for a Test
445(4)
Testing the Difference Between Two Population Means: Independent Samples
449(10)
Testing the Difference Between Two Population Means: Matched Pairs
459(6)
Testing a Population Proportion
465(3)
Testing the Difference Between Two Population Proportions
468(5)
Testing a Population Variance
473(3)
Testing the Ratio of Two Population Variances
476(6)
Summary
482(13)
Testing Means
489(6)
Categorical Data Analysis
495(36)
Categorical Data and Multinomial Probabilities
496(1)
Estimating Category Probabilities in a One-Way Table
496(5)
Testing Category Probabilities in a One-Way Table
501(4)
Inferences About Category Probabilities in a Two-Way (Contingency) Table
505(10)
Contingency Tables with Fixed Marginal Totals
515(6)
Summary
521(10)
Contingency Table Analysis
527(4)
Simple Linear Regression
531(68)
Introduction
532(1)
A Simple Linear Regression Model: Assumptions
533(3)
Estimating β0 and β1: The Method of Least Squares
536(11)
Properties of the Least Squares Estimators
547(3)
An Estimator of σ2
550(3)
Assessing the Utility of the Model: Making Inferences About the Slope β1
553(8)
The Coefficient of Correlation
561(5)
The Coefficient of Determination
566(6)
Using the Model for Estimation and Prediction
572(9)
Simple Linear Regression on the Computer
581(5)
Summary
586(13)
Simple Linear Regression and Correlation
594(5)
Multiple Regression Analysis
599(100)
General Linear Models
600(3)
Model Assumptions
603(1)
Fitting the Model: The Method of Least Squares
603(2)
The Least Squares Equations and Their Solution
605(7)
Properties of the Least Squares Estimators
612(1)
Estimating σ2 the Variance of ε
613(2)
Confidence Intervals and Tests of Hypotheses for β0, β1, ..., βk
615(10)
Assessing Model Adequacy
625(13)
A Confidence Interval for E(y)
638(7)
A Prediction Interval for a Future Value of y
645(3)
Checking Assumptions: Residual Analysis
648(25)
Some Pitfalls: Estimability, Multicollinearity, and Extrapolation
673(11)
Summary
684(15)
Multiple Regression and Residual Analysis
696(3)
Model Building
699(90)
Why Model Building Is Important
700(1)
The Two Types of Independent Variables: Quantitative and Qualitative
701(2)
Models with a Single Quantitative Independent Variable
703(9)
Models with Two Quantitative Independent Variables
712(9)
Coding Quantitative Independent Variables (Optional)
721(6)
Tests for Comparing Nested Models
727(8)
Models with One Qualitative Independent Variable
735(6)
Comparing the Slopes of Two or More Lines
741(14)
Comparing Two or More Response Curves
755(5)
Stepwise Regression
760(8)
Model Building: An Example
768(9)
Summary
777(12)
Stepwise Regression
785(4)
Analysis of Variance for Designed Experiments
789(130)
Introduction
790(1)
Experimental Design: Terminology
791(1)
Controlling the Information in an Experiment
792(2)
Noise-Reducing Designs
794(7)
Volume-Increasing Designs
801(6)
Selecting the Sample Size
807(3)
The Logic Behind an Analysis of Variance
810(3)
ANOVA for Completely Randomized Designs
813(15)
ANOVA for Randomized Block Designs
828(15)
ANOVA for Two-Factor Factorial Experiments
843(21)
ANOVA for a k-Way Classification of Data (Optional)
864(11)
ANOVA for Nested Sampling Designs (Optional)
875(15)
Procedures for Making Multiple Comparisons of Treatment Means
890(8)
Checking ANOVA Assumptions
898(4)
Summary
902(17)
Analysis of Variance
915(4)
Nonparametric Statistics
919(62)
Introduction
920(2)
Testing for Location of a Single Population
922(6)
Comparing Two Populations: Independent Random Samples
928(9)
Comparing Two Populations: Matched-Pairs Design
937(8)
Comparing Three or More Populations: Completely Randomized Design
945(7)
Comparing Three or More Populations: Randomized Block Design
952(5)
Nonparametric Regression
957(9)
Summary
966(15)
Nonparametric Tests
974(7)
Statistical Process and Quality Control
981(54)
Total Quality Management
982(1)
Variable Control Charts
982(7)
Control Chart for Means: x-Chart
989(10)
Control Chart for Process Variation: R-Chart
999(3)
Detecting Trends in a Control Chart: Runs Analysis
1002(2)
Control Chart for Percent Defectives: p-Chart
1004(5)
Control Chart for the Number of Defects per Item: c-Chart
1009(4)
Tolerance Limits
1013(5)
Acceptance Sampling for Defectives
1018(6)
Other Sampling Plans (Optional)
1024(1)
Evolutionary Operations (Optional)
1025(2)
Summary
1027(8)
Control Charts
1030(5)
Product and System Reliability
1035(30)
Introduction
1036(1)
Failure Time Distributions
1036(2)
Hazard Rates
1038(4)
Life Testing: Censored Sampling
1042(1)
Estimating the Parameters of an Exponential Failure Time Distribution
1043(5)
Estimating the Parameters of a Weibull Failure Time Distribution
1048(5)
System Reliability
1053(6)
Summary
1059(6)
APPENDIX I Matrix Algebra 1065(20)
Matrices and Matrix Multiplication
1066(6)
Identity Matrices and Matrix Inversion
1072(3)
Solving Systems of Simultaneous Linear Equations
1075(3)
A Procedure for Inverting a Matrix
1078(7)
APPENDIX II Useful Statistical Tables 1085(40)
Table 1 Cumulative Binomial Probabilities
1087(4)
Table 2 Exponentials
1091(1)
Table 3 Cumulative Poisson Probabilities
1092(2)
Table 4 Normal Curve Areas
1094(1)
Table 5 Gamma Function
1095(1)
Table 6 Random Numbers
1096(3)
Table 7 Critical Values of Student's t
1099(1)
Table 8 Critical Values of X2
1100(2)
Table 9 Percentage Points of the F Distribution, α = .10
1102(2)
Table 10 Percentage Points of the F Distribution, α = .05
1104(2)
Table 11 Percentage Points of the F Distribution, α = .025
1106(2)
Table 12 Percentage Points of the F Distribution, α = .01
1108(2)
Table 13 Percentage Points of the Studentized Range q(p, v), α = .05
1110(2)
Table 14 Percentage Points of the Studentized Range q(p, v), α = .01
1112(2)
Table 15 Critical Values of TL and TU for the Wilcoxon Rank Sum Test: Independent Samples
1114(1)
Table 16 Critical Values of TO in the Wilcoxon Matched-Pairs Signed Rank Test
1115(1)
Table 17 Critical Values of Spearman's Rank Correlation Coefficient
1116(1)
Table 18 Critical Values of C for the Theil Zero-Slope Test
1117(4)
Table 19 Factors Used When Constructing Control Charts
1121(1)
Table 20 Values of K for Tolerance Limits for Normal Distributions
1122(1)
Table 21 Sample Size n for Nonparametric Tolerance Limits
1123(1)
Table 22 Sample Size Code Letters: MIL-STD-105D
1123(1)
Table 23 A Portion of the Master Table for Normal Inspection (Single Sampling): MIL-STD-105D
1124(1)
APPENDIX III DDT Analyses on Fish Samples, Tennessee River, Alabama 1125(4)
APPENDIX IV Central Processing Unit (CPU) Times of 1,000 Computer Jobs 1129(4)
APPENDIX V Percentage Iron Content for 390 Iron-Ore Specimens 1133(4)
APPENDIX VI Federal Trade Commission Rankings of Domestic Cigarette Brands 1137(8)
APPENDIX VII ASP Tutorial 1145(6)
Answers to the Exercises 1151(26)
Index 1177


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