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Probability and Statistics for Engineers and Scientists
ISBN: 9780024242013 | 0024242012
Edition: 5thPublisher: Prentice Hall Professional Technical Reference
Pub. Date: 1/1/1993
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This classic book provides a rigorous introduction to basic probability theory and statistical inference that is well motivated by interesting, relevant applications. The new edition features many new, real-data based exercises and examples, an increased emphasis on the analysis of statistical output and greater use of graphical techniques and statistical methods in quality improvement.
| Preface | |
| Introduction to Statistics and Data Analysis | |
| Overview: Statistical Inference, Samples, Populations, and Experimental Design | |
| The Role of Probability | |
| Sampling Procedures | |
| Collection of Data | |
| Measures of Location: The Sample Mean | |
| Measures of Variability | |
| Discrete and Continuous Data | |
| Statistical Mod... MORE | |
| Graphical Methods and Data Description | |
| Probability | |
| Sample Space | |
| Events | |
| Counting Sample Points | |
| Probability of an Event | |
| Additive Rules | |
| Conditional Probability | |
| Multiplicative Rules | |
| Bayes' Rule | |
| Random Variables and Probability Distributions | |
| Concept of a Random Variable | |
| Discrete Probability Distributions | |
| Continuous Probability Distributions | |
| Joint Probability Distributions | |
| Mathematical Expectation | |
| Mean of a Random Variable | |
| Variance and Covariance | |
| Means and Variances of Linear Combinations of Random Variables | |
| Chebyshev's Theorem | |
| Some Discrete Probability Distributions | |
| Discrete Uniform Distribution | |
| Binomial and Multinomial Distributions | |
| Hypergeometric Distribution | |
| Negative Binomial and Geometric Distributions | |
| Poisson Distribution and the Poisson Process | |
| Some Continuous Probability Distributions | |
| Continuous Uniform Distribution | |
| Normal Distribution | |
| Areas Under the Normal Curve | |
| Applications of the Normal Distribution | |
| Normal Approximation to the Binomial | |
| Gamma and Exponential Distributions | |
| Applications of the Exponential and Gamma Distributions | |
| Chi-Squared Distribution | |
| Lognormal Distribution | |
| Weibull Distribution | |
| Functions of Random Variables (Optional) | |
| Transformations of Variables | |
| Moments and Moment-Generating Functions | |
| Fundamental Sampling Distributions and Data Descriptions | |
| Random Sampling | |
| Some Important Statistics | |
| Data Displays and Graphical Methods | |
| Sampling Distributions | |
| Sampling Distribution of Means | |
| Sampling Distribution of S2 | |
| T-Distribution | |
| F-Distribution | |
| One- and Two-Sample Estimation Problems | |
| Statistical Inference | |
| Classical Methods of Estimation | |
| Single Sample: Estimating the Mean | |
| Standard Error of a Point Estimate | |
| Prediction Interval | |
| Tolerance Limits | |
| Two Samples: Estimating the Difference Between Two Means | |
| Paired Observations | |
| Single Sample: Estimating a Proportion | |
| Two Samples: Estimating the Difference Between Two Proportions | |
| Single Sample: Estimating the Variance | |
| Two Samples: Estimating the Ratio of Two Variances | |
| Bayesian Methods of Estimation (Optional) | |
| Maximum Likelihood Estimation (Optional) | |
| One- and Two-Sample Tests of Hypotheses | |
| Statistical Hypotheses: General Concepts | |
| Testing a Statistical Hypothesis | |
| One- and Two-Tailed Tests/ The Use of P/D-Values for Decision Making | |
| Single Sample: Tests Concerning a Single Mean (Variance Known) | |
| Relationship to Confidence Interval Estimation | |
| Single Sample: Tests on a Single Mean (Variance Unknown) | |
| Two Samples: Tests on Two Means | |
| Choice of Sample Size for Testing Means | |
| Graphical Methods for Comparing Means | |
| One Sample: Test on a Single Proportion | |
| Two Samples: Tests on Two Proportions | |
| One- and Two-Sample Tests Concerning Variances | |
| Goodness-of-Fit Test | |
| Test for Independence (Categorical Data) | |
| Test for Homogeneity | |
| Testing for Several Proportions | |
| Two-Sample Case Study | |
| Simple Linear Regression and Correlation | |
| Introduction to Linear Regression | |
| Simple Linear Regression | |
| Least Squares and The Fitted Model | |
| Properties of the Least Squares Estimators | |
| Inferences Concerning the Regression Coefficients | |
| Prediction | |
| Choice of a Regression Model | |
| Analysis-of-Variance Approach | |
| Test for Linearity of Regression: Data with Repeated Observations | |
| Data Plots and Transformations | |
| Simple Linear Regression Case Study | |
| Correlation | |
| Multiple Linear Regression and Certain Nonlinear Regression Models | |
| Estimating the Coefficients | |
| Linear Regression Model Using Matrices (Optional) | |
| Properties of the Least Squares Estimators | |
| Inferences in Multiple Linear Regression | |
| Choice of a Fitted Model Through Hypothesis Testing | |
| Special Case of Orthogonality (Optional) | |
| Categorical or Indicator Variables | |
| Sequential Methods for Model Selection | |
| Study of Residuals and Violation of Assumptions | |
| Cross Validation, Cvp, and Other Criteria for Model Selection | |
| Special Nonlinear Models for Nonideal Conditions | |
| One Factor Experiments: General | |
| Analysis-of-Variance Technique | |
| The Strategy of Experimental Design | |
| One-Way Analysis of Variance: Completely Randomized Design | |
| Tests for the Equality of Several Variances | |
| Single-Degree-of-Freedom Comparisons | |
| Multiple Comparisons | |
| Comparing Treatments with a Control | |
| Comparing a Set of Treatments in Blocks | |
| Randomized Complete Block Designs | |
| Graphical Methods and Further Diagnostics | |
| Latin Squares (Optional) | |
| Random Effects Models | |
| Power of Analysis-of-Variance Tests | |
| Case Study | |
| Factorial Experiments (Two or More Factors) | |
| Interaction and the Two-Factor Experiment | |
| Two-Factor Analysis of Variance | |
| Graphical Analysis in the Two-Factor Problem | |
| Three-Factor Experiments | |
| Model II and III Factorial Experiments | |
| Choice of Sample Size | |
| 2k Factorial Experiments and Fractions | |
| 15 | |
| Analysis of Variance and the Calculation of Effects | |
| Nonreplicated 2k Factorial Experiment | |
| Injection Molding Case Study | |
| Factorial Experiments in Incomplete Blocks | |
| Partial Confounding | |
| Factorial Experiments in a Regression Setting | |
| The Orthogonal Design | |
| Fractional Factorial Experiments | |
| Analysis of Fractional Factorial Experiments | |
| Higher Fractions and Screening Designs | |
| Construction of Resolution III and IV Designs with 8,16, and 32 Design Points | |
| Other Two-Level Resolution III Designs | |
| The Plackett-Burman Designs | |
| Taguchi's Robust Parameter Design | |
| Nonparametric Statistics | |
| Nonparametric Tests | |
| Sign Test | |
| Signed-Rank Test | |
| Rank-Sum Test | |
| Kruskal-Wallis Test | |
| Tolerance Limits | |
| Rank Correlation Coefficient | |
| Statistical Quality Control | |
| Nature of the Control Limits | |
| Purposes of the Control Chart | |
| Control Charts for Variables | |
| Control Charts for Attributes | |
| Cusum Control Charts | |
| Bibliography | |
| Appendix: Statistical Tables and Proofs of Some Theoretical Results | |
| Table of Contents provided by Publisher. All Rights Reserved. |
