Probability & Statistics for Engineers & Scientists, MyLab Statistics Update with MyLab Statistics plus Pearson eText -- Access Card Package

by Walpole, Ronald E.; Myers, Raymond H.; Myers, Sharon L.; Ye, Keying

• ISBN13: 9780134468914
• ISBN10: 0134468910
• eBook ISBN(s): 9780134432656
• Edition: 9th
• Format: Package
• Copyright: 2016-03-10
• Publisher: Pearson
• More Book Details

Summary

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This package includes MyStatLab^®.  

This classic text provides a rigorous introduction to basic probability theory and statistical inference, with a unique balance between theory and methodology. Interesting, relevant applications use real data from actual studies, showing how the concepts and methods can be used to solve problems in the field. This revision focuses on improved clarity and deeper understanding.

 

This latest edition is also available in as an enhanced Pearson eText. This exciting new version features an embedded version of StatCrunch, allowing students to analyze data sets while reading the book.

 

 

Personalize learning with MyStatLab

MyStatLab^™ is an online homework, tutorial, and assessment program designed to work with this text to engage students and improve results. Within its structured environment, students practice what they learn, test their understanding, and pursue a personalized study plan that helps them absorb course material and understand difficult concepts.

 

0134468910 / 9780134468914 Probability & Statistics for Engineers & Scientists, MyStatLab Update with MyStatLab plus Pearson eText -- Access Card Package 9/e

 

Package consists of:   

0134115856 / 9780134115856 Probability & Statistics for Engineers & Scientists, MyStatLab Update

0321847997 / 9780321847997 My StatLab Glue-in Access Card

032184839X / 9780321848390 MyStatLab Inside Sticker for Glue-In Packages

Table of Contents

Preface

1. Introduction to Statistics and Data Analysis

1.1 Overview: Statistical Inference, Samples, Populations, and the Role of Probability

1.2 Sampling Procedures; Collection of Data

1.3 Measures of Location: The Sample Mean and Median

           Exercises

1.4 Measures of Variability

           Exercises

1.5 Discrete and Continuous Data

1.6 Statistical Modeling, Scientific Inspection, and Graphical Methods 19

1.7 General Types of Statistical Studies: Designed Experiment,

Observational Study, and Retrospective Study

           Exercises

2. Probability

2.1 Sample Space

2.2 Events

           Exercises

2.3 Counting Sample Points

           Exercises

2.4 Probability of an Event

2.5 Additive Rules

           Exercises

2.6 Conditional Probability, Independence and Product Rules

           Exercises

2.7 Bayes’ Rule

           Exercises

           Review Exercises

2.8 Potential Misconceptions and Hazards; Relationship to Material in Other Chapters

3. Random Variables and Probability Distributions

3.1 Concept of a Random Variable

3.2 Discrete Probability Distributions

3.3 Continuous Probability Distributions

           Exercises

3.4 Joint Probability Distributions

           Exercises

           Review Exercises

3.5 Potential Misconceptions and Hazards; Relationship to Material in Other Chapters

4. Mathematical Expectation

4.1 Mean of a Random Variable

           Exercises

4.2 Variance and Covariance of Random Variables

           Exercises

4.3 Means and Variances of Linear Combinations of Random Variables 127

4.4 Chebyshev’s Theorem

           Exercises

           Review Exercises

4.5 Potential Misconceptions and Hazards; Relationship to Material in Other Chapters

5. Some Discrete Probability Distributions

5.1 Introduction and Motivation

5.2 Binomial and Multinomial Distributions

           Exercises

5.3 Hypergeometric Distribution

           Exercises

5.4 Negative Binomial and Geometric Distributions

5.5 Poisson Distribution and the Poisson Process

           Exercises

           Review Exercises

5.6 Potential Misconceptions and Hazards; Relationship to Material in Other Chapters

6. Some Continuous Probability Distributions

6.1 Continuous Uniform Distribution

6.2 Normal Distribution

6.3 Areas under the Normal Curve

6.4 Applications of the Normal Distribution

           Exercises

6.5 Normal Approximation to the Binomial

           Exercises

6.6 Gamma and Exponential Distributions

6.7 Chi-Squared Distribution

6.8 Beta Distribution

6.9 Lognormal Distribution (Optional)

6.10 Weibull Distribution (Optional)

           Exercises

           Review Exercises

6.11 Potential Misconceptions and Hazards; Relationship to Material in Other Chapters

7. Functions of Random Variables (Optional)

7.1 Introduction

7.2 Transformations of Variables

7.3 Moments and Moment-Generating Functions

           Exercises

8. Sampling Distributions and More Graphical Tools

8.1 Random Sampling and Sampling Distributions

8.2 Some Important Statistics

           Exercises

8.3 Sampling Distributions

8.4 Sampling Distribution of Means and the Central Limit Theorem

           Exercises

8.5 Sampling Distribution of S ²

8.6 t-Distribution

8.7 F-Distribution

8.8 Quantile and Probability Plots

           Exercises

           Review Exercises

8.9 Potential Misconceptions and Hazards; Relationship to Material in Other Chapters

9. One- and Two-Sample Estimation Problems

9.1 Introduction

9.2 Statistical Inference

9.3 Classical Methods of Estimation

9.4 Single Sample: Estimating the Mean

9.5 Standard Error of a Point Estimate

9.6 Prediction Intervals

9.7 Tolerance Limits

           Exercises

9.8 Two Samples: Estimating the Difference Between Two Means

9.9 Paired Observations

           Exercises

9.10 Single Sample: Estimating a Proportion

9.11 Two Samples: Estimating the Difference between Two Proportions

           Exercises

9.12 Single Sample: Estimating the Variance

9.13 Two Samples: Estimating the Ratio of Two Variances

           Exercises

9.14 Maximum Likelihood Estimation (Optional)

           Exercises

           Review Exercises

9.15 Potential Misconceptions and Hazards; Relationship to Material in Other Chapters

10. One- and Two-Sample Tests of Hypotheses

10.1 Statistical Hypotheses: General Concepts

10.2 Testing a Statistical Hypothesis

10.3 The Use of P-Values for Decision Making in Testing Hypotheses

           Exercises

10.4 Single Sample: Tests Concerning a Single Mean

10.5 Two Samples: Tests on Two Means

10.6 Choice of Sample Size for Testing Means

10.7 Graphical Methods for Comparing Means

           Exercises

10.8 One Sample: Test on a Single Proportion

10.9 Two Samples: Tests on Two Proportions

           Exercises

10.10 One- and Two-Sample Tests Concerning Variances

           Exercises

10.11 Goodness-of-Fit Test

10.12 Test for Independence (Categorical Data)

10.13 Test for Homogeneity

10.14 Two-Sample Case Study

           Exercises

           Review Exercises

10.15 Potential Misconceptions and Hazards; Relationship to Material in Other Chapters

11. Simple Linear Regression and Correlation

11.1 Introduction to Linear Regression

11.2 The Simple Linear Regression Model

11.3 Least Squares and the Fitted Model

           Exercises

11.4 Properties of the Least Squares Estimators

11.5 Inferences Concerning the Regression Coefficients

11.6 Prediction

           Exercises

11.7 Choice of a Regression Model

11.8 Analysis-of-Variance Approach

11.9 Test for Linearity of Regression: Data with Repeated Observations 416

           Exercises

11.10 Data Plots and Transformations

11.11 Simple Linear Regression Case Study

11.12 Correlation

           Exercises

           Review Exercises

11.13 Potential Misconceptions and Hazards; Relationship to Material in Other Chapters

12. Multiple Linear Regression and Certain Nonlinear Regression Models

12.1 Introduction

12.2 Estimating the Coefficients

12.3 Linear Regression Model Using Matrices

           Exercises

12.4 Properties of the Least Squares Estimators

12.5 Inferences in Multiple Linear Regression

           Exercises

12.6 Choice of a Fitted Model through Hypothesis Testing

12.7 Special Case of Orthogonality (Optional)

           Exercises

12.8 Categorical or Indicator Variables

           Exercises

12.9 Sequential Methods for Model Selection

12.10 Study of Residuals and Violation of Assumptions

12.11 Cross Validation, C_p , and Other Criteria for Model Selection

           Exercises

12.12 Special Nonlinear Models for Nonideal Conditions

           Exercises

           Review Exercises

12.13 Potential Misconceptions and Hazards; Relationship to Material in Other Chapters

13. One-Factor Experiments: General

13.1 Analysis-of-Variance Technique

13.2 The Strategy of Experimental Design

13.3 One-Way Analysis of Variance: Completely Randomized Design (One-Way ANOVA)

13.4 Tests for the Equality of Several Variances

           Exercises

13.5 Multiple Comparisons

           Exercises

13.6 Comparing a Set of Treatments in Blocks

13.7 Randomized Complete Block Designs

13.8 Graphical Methods and Model Checking

13.9 Data Transformations In Analysis of Variance)

           Exercises

13.10 Random Effects Models

13.11 Case Study

           Exercises

           Review Exercises

13.12 Potential Misconceptions and Hazards; Relationship to Material in Other Chapters

14. Factorial Experiments (Two or More Factors)

14.1 Introduction

14.2 Interaction in the Two-Factor Experiment

14.3 Two-Factor Analysis of Variance

           Exercises

14.4 Three-Factor Experiments

           Exercises

14.5 Factorial Experiments for Random Effects and Mixed Models

           Exercises

           Review Exercises

14.6 Potential Misconceptions and Hazards; Relationship to Material in Other Chapters

15. 2 ^k Factorial Experiments and Fractions

15.1 Introduction

15.2 The 2 ^k Factorial: Calculation of Effects and Analysis of Variance 598

15.3 Nonreplicated 2 ^k Factorial Experiment

           Exercises

15.4 Factorial Experiments in a Regression Setting

15.5 The Orthogonal Design

           Exercises

15.6 Fractional Factorial Experiments

15.7 Analysis of Fractional Factorial Experiments

           Exercises

15.8 Higher Fractions and Screening Designs

15.9 Construction of Resolution III and IV Designs

15.10 Other Two-Level Resolution III Designs; The Plackett-Burman Designs

15.11 Introduction to Response Surface Methodology

15.12 Robust Parameter Design

           Exercises

           Review Exercises

15.13 Potential Misconceptions and Hazards; Relationship to Material in Other Chapters

16. Nonparametric Statistics

16.1 Nonparametric Tests

16.2 Signed-Rank Test

           Exercises

16.3 Wilcoxon Rank-Sum Test

16.4 Kruskal-Wallis Test

           Exercises

16.5 Runs Test

16.6 Tolerance Limits

16.7 Rank Correlation Coefficient

           Exercises

           Review Exercises

17. Statistical Quality Control

17.1 Introduction

17.2 Nature of the Control Limits

17.3 Purposes of the Control Chart

17.4 Control Charts for Variables

17.5 Control Charts for Attributes

17.6 Cusum Control Charts

           Review Exercises

18 Bayesian Statistics

18.1 Bayesian Concepts

18.2 Bayesian Inferences

18.3 Bayes Estimates Using Decision Theory Framework

           Exercises

Bibliography

A. Statistical Tables and Proofs

B. Answers to Odd-Numbered Non-Review Exercises

Index