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工程师和科学家实用统计分析:基于计算机的方法 英文版

工程师和科学家实用统计分析:基于计算机的方法 英文版

定 价:¥65.00

作 者: J.Wesiey Barnes著
出版社: 清华大学出版社
丛编项: 国外大学优秀教材工业工程系列
标 签: 暂缺

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ISBN: 9787900641977 出版时间: 2002-06-01 包装: 精装
开本: 23cm+光盘1片 页数: 424 字数:  

内容简介

  《工程师和科学家实用统计分析》是第一本从现代计算机观点出发的工程统计学教材。通过集成教材中内容宽广的软件程序,结合在工程和科研中的应用,为学生讲授概率和统计学的概念。本书包含独特、全面及用户友好的软件包(用于PC机或苹果机)和随书的用户手册,其特色是以应用为取向,而对大多数理论问题和控讨较为直观。通过精心设计的章节式学习方式和各种练习,帮助学生在充分学习使用软件的过程中掌握各章的内容,并对所有出现的假设检验中的有效样本进行了完全和详细的统计处理。本书的主要内容包括:多元回归分析、离散随机变量的卷积和变换、双变量概率分布、假设检验的操作特性曲线、统计过程控制和非参数统计分析等。

作者简介

暂缺《工程师和科学家实用统计分析:基于计算机的方法 英文版》作者简介

图书目录

List of Figures
List Of Tables
Preface
1 Introduction
2 Probability: Fundamental Concepts and Operational Rules
2.1 Repeatable Experiments and Sample Spaces
2.2 Events and the Venn Diagram
2.3 Probability and Operational Rules
2.4 Conditional Probability and Statistical Independence
2.5 Bayes'' Formula
2.6 Counting Techniquesf Trees, Combinations, and Permutations
Exercises
Computer-Based Exercises
3 Discrete Random Variables
3.1 Random Variables and General Properties of Probability Distributions
3.2 The Binomial Distribution
3.3 Some Popular Discrete Distributions and Their Relationships
3.4 A Suggestion for Solving Problems Involving Discrete Random Variables
3.5 Discrete Bivariate Probability Distribution Functions
Exercises
Computer-Based Exercises
4 Continuous Random Variables
4.1 General Properties of Continuous Random Variables
4.2 The Normal Distribution
4.3 Some Popular Continuous Distributions and Their ReIationships
4.4 Continuous Bivariate Probability Density Functions
Exercises
Computer-Based Exercises
5 The Mean, Variance, Expected Value Operator, and Other
Functions of Random Variables
5.1 Introduction
5.2 Measures of Centrality: The Mean, Median, and Mode
5.3 Measures of Variability: The Range and the Variance
5.4 The Expected Value Operator
5.5 Two Additional Measures of a Probability Distribution Function:Skewness and Kurtosis
5.6 The Covariance and Correlation of Bivariate Distribution Functions
5.7 Functions of One or More Random Variables
5.8 A Comment about the Road Ahead
Exercises
6 Classification and Description of Sample Data
6.1 Introduction
6.2 The Frequency Table and Its Outgrowths
6.3 Graphical Presentations of the Frequency Table
6.4 Sample Estimates
6.5 Some Suggestions for Further Study
Exercises
7 Sampling Distributions: Random Sampling, the Sample Mean and Sample Variance, and the Central Limit Theorem
7.1 Random Sampling from Finite and Infinite Populations
7.2 The Distribution of the Sample Mean, X
7.3 The Distribution of the Sample Variance, S2
Exercises
8 Point and Interval Estimators and the Estimation of the Mean and the Variance
8.1 Point Estimators
8.2 Interval Estimators
8.3 Interval Estimates for Population Means
8.4 Determining an Adequate Sample Size for Interval Estimation of a Mean
8.5 Confidence Intervals for the Variance
8.6 Estimating Proportions
8.7 The Three General Types of Confidence Intervals
Exercises
9 Hypothesls Tests about a Single Mean, a Single Proportion,
or a Single Variance
9.1 Introduction
9.2 Hypothesis Tests about a Single Mean
9.3 Hypothesis Tests about a Single Proportion
9.4 Hypothesis Tests about a Single Variance
9.5 Some Comments on the Difference between Statistical Significance and Practical Significance
Exercises
10 Hypehesis Tests for bo Means, two Variances, or two Proportions
10.1 Tests Comparing Two Means When o1 and o2 Are Known
10.2 Tests Comparing Two Means When o1 and o2 Are Unknown
10.3 Tests Comparing Two Means When the Data Are Paired
10.4 Tests Concerning Two Variances
10.5 Hypothesis Tests about Two Proportions
Exercises
11 Fitting Equations to Data, Part I: Simple Unear Regression Analysis and CurviIinear Regression Analysis
11.1 Introduction
11.2 The Mathematical Model for Simple Linear Regression Analysis
11.3 Obtaining the Best Estimates of Bo and B1
11.4 The MultipIe CorreIation Coefficient Squared, r2
11.5 A Hypothesis Test for the Significance of the Fitted Line
11.6 The Construction of Confjdence Intervals about Bo, B1, the Mean of Y, and a Predicted Value of Y
11.7 The Correlation Coefficient and a Joint Confidence Region for Bo and B1
11.8 Graphical Methods of Investigating Data Structure in SLR
11.9 The Study of Sample Residuals in SLR
11.10 Curvilinear Regression
Exercises
12 Fitting Equations to Data, Part II: Multivariate Regression Analysis
12.1 Intbouction
12.2 Estimating the Parameter Values in MLR
12.3 Some Useful Theoretical Properties of MLR
12.4 The Variance-Covariance and Correlation Matrices of B
12.5 Univariate Confidence Intervals on the B1 and on predicted values Of y
12.6 Determining Whether a Fit is Adequate and Comparing Competing Models
12.7 The General Linear Model and the Other Side of the Coin
Exercises
13 Hypothesis Tests for two or More Means: Analysis Of Variance--Single-Factor besigns
13.1 Introduction
13.2 Completely Randomized Single-Factor Experiments
13.3 How to Determine Which Means Differ When Hor the Completely Randomized Single-Factor Design
13.5 The Randomized Block Design: A Single-Factor Design with One Restriction on Randomization
13.6 Some Comments on Additional Single-Factor Designs and on Missing Data
Exercises
14 Factorlal Analysis of Variance
14.1 Introduction
14.2 A Two-Factor Factorial ANOVA Design
14.3 Higher-Order Multifactor Faotorial Designs
Exercises
15 An Introduction to Statistical Ouality Control
15.1 Introduction
15.2 A Control Chart for Variables: The k-R Chart
15.3 Control Charts for Attributes
15.4 Acceptance Sampling: Construction of Sampling Plans and Their Uses
Exercises
16 Some Additional Methods of Data Analysis
16.1 Introduction
16.2 The x2 Test for Goodness of Fit
16.3 A Distribution-Free Alternative to the t Test: The Wilcoxon Signed Rank Test
16.4 A Distribution-Free Alternative to the Two-Sample t Test: The Wilcoxon Rank Sum Test
16.5 A Distribution-Free Alternative to the Completely Randomized Single-Factor ANOVA: The Kruskal-Wallis Test
Exercises
Raterences and Suggested Readings
Statistcal Tables
Answers to Selected Exerclses
Index
《用户手册》的目录
PREFACE
1. Introduction
II. Simulation of a Finite Diacrete Sample Space
III. Evaluating Factorlale, Permutatione, & Combinatione
IV. Distribution Evaluators
A. Continuous Distribution Evaluators: The Uniform, Normal,Exponential, Gamma, Ghi-Square, t, F, Lognormal, Beta, and Weibull Distributions
B. Discrete Distribution Evaluators: The Binomial, Hypergeometric, Poisson. Geometric, and Negative Binomial Distributione
V Plotting Probability Distribution Fundions and Other Univariate Functione
A. Plotting the Probability Distribution Functions of Tables 3.2 and 4.1
B. Plotting a User-Specified Continuous Probability Distribution
Function or Any User-Specified Continuous Univariate
Function
C. Plotting a User-Specified Discrete Probability Distribution Function
VI. Convolution and Tranaformation of Disctete Probabllity Distributions
A. Transformation of User-Specified Discrete Probability Distributions
B. Convolution and Power Transtormation of User-Specified Discrete Probability Distributions
VII. Basic Analysis of a User-Provided Data Set
VIII. Simulation of the Probability Distributions of Tables 9.2 and 4.1
IX. The Setting of Confidence Intervals
A. Confidence Intervals for One Mean
B. Confidence Intervals for One Variance
C. Confidence Intervals for One Proportion
X. The Performance of Hypothesia Teste
A. Hypothesis Tests for One Mean
B. Hypothesis Tests for One Variance
C. Hypothesis Tests for One Proportion
D. Hypothesis Tests for Two Means
E. Hypothesis Tests for Two Variances
F. Hypothesis Tests for Two Proportions
XI. The Formulation of Operating Characterietie Curves for Teste of Hypotheses
A. Operating Characteristic Curves for Hypothesis Tests about Means
B. Operating Characteristic Curves for Hypothesis Tests about One Variance
C. Operating Characteristic Curves for Hypothesis Tests about Two Variances
D. Operating Charaderistic Curves for Hypotheses Tests about One Proportion
E. Beta Errors for Hypothesis Tests about Two Proportions
XII. Regression Analyels
A. Bivariate Regression Anaglsis
B. Multivariate Regression Analysis
C. Transformation of Regression Data
XIII. Analyels of Variance
A. One-Factor Completely Randomized Analysis of Variance
B. Two-Factor Blocked Analysis of Variance
C. Two-Factor Factorial Analysis of Variance
D. Three-Factor Factorial Analysis of Variance
E. Operating Characteristic Curves for Analysis of Variance
XIV. Statistical Quality Control
A. The x-R Chart
B. The p Chart
G. Operating Characteristic Curves for Single Sampling Plans
XV. The X Goodness of Fit Test and Distribution Free Methode
A. The X Goodness of Fit Test
B. The Wilcoxon Signed Rank Test
C. The Wilcoxon Rank Sum Test Proram
D. The Kruskal-Wallis Test
XVI. The Full.Sereen Data Editor Appendixes
A. Structure of the Data Sets Used by the Programs in the Library
B. List of Programs List of Data Files
C. Extension Names for Data Files

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