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## Details

Genre/Form: | Manuels d'enseignement supérieur |
---|---|

Material Type: | Internet resource |

Document Type: | Book, Internet Resource |

All Authors / Contributors: |
Anthony J Hayter |

ISBN: | 0495107573 9780495107576 0495107603 9780495107606 0495108782 9780495108788 |

OCLC Number: | 71250527 |

Notes: | Includes index. "This CD-ROM contains datasets formatted for ASCII, Microsoft Excel, SAS, JMP, SPSS, and MINITAB." |

Description: | xviii, 812 p. : col. ill. ; 26 cm. + 1 CD-ROM (4 3/4 in.) |

Details: | Minimum system requirements: PC: Windows 2000, XP (not NT), Pentium II 233 MHz, 32MB RAM (64MB recommended); Mac: MAC OS X or later, PowerPC processor or later, 64MB RAM; both: 800 x 600, 16-bit high-color display, 8x CD-ROM. |

Contents: | 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 ss1. 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. |

Other Titles: | Probability & statistics for engineers and scientists |

Responsibility: | Anthony J. Hayter. |

More information: |

### Abstract:

## Reviews

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Publisher Synopsis

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 ss1. 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. Read more...

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