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Probability and statistics for engineering and the sciences / Jay L. Devore

By: Devore, Jay LMaterial type: TextTextLanguage: English Publisher: New Delhi ; Cengage Learning, 2017Edition: 9th edDescription: xiv, 715 pages, various paging's : illustrations (black and white) ; 26 cmISBN: 9789353506247Subject(s): Mathematical statistics | ProbabilitiesDDC classification: 519.2
Contents:
1. OVERVIEW AND DESCRIPTIVE STATISTICS. Populations, Samples, and Processes. Pictorial and Tabular Methods in Descriptive Statistics. Measures of Location. Measures of Variability. 2. PROBABILITY. Sample Spaces and Events. Axioms, Interpretations, and Properties of Probability. Counting Techniques. Conditional Probability. Independence. 3. DISCRETE RANDOM VARIABLES AND PROBABILITY DISTRIBUTIONS. Random Variables. Probability Distributions for Discrete Random Variables. Expected Values. The Binomial Probability Distribution. Hypergeometric and Negative Binomial Distributions. The Poisson Probability Distribution. 4. CONTINUOUS RANDOM VARIABLES AND PROBABILITY DISTRIBUTIONS. Probability Density Functions. Cumulative Distribution Functions and Expected Values. The Normal Distribution. The Exponential and Gamma Distributions. Other Continuous Distributions. Probability Plots. 5. JOINT PROBABILITY DISTRIBUTIONS AND RANDOM SAMPLES. Jointly Distributed Random Variables. Expected Values, Covariance, and Correlation. Statistics and Their Distributions. The Distribution of the Sample Mean. The Distribution of a Linear Combination. 6. POINT ESTIMATION. Some General Concepts of Point Estimation. Methods of Point Estimation. 7. STATISTICAL INTERVALS BASED ON A SINGLE SAMPLE. Basic Properties of Confidence Intervals. Large-Sample Confidence Intervals for a Population Mean and Proportion. Intervals Based on a Normal Population Distribution. Confidence Intervals for the Variance and Standard Deviation of a Normal Population. 8. TESTS OF HYPOTHESIS BASED ON A SINGLE SAMPLE. Hypotheses and Test Procedures. z Tests for Hypotheses About a Population Mean. The One-Sample t Test. Tests Concerning a Population Proportion. Further Aspects of Hypothesis Testing. 9. INFERENCES BASED ON TWO SAMPLES. z Tests and Confidence Intervals for a Difference between Two Population Means. The Two-Sample t Test and Confidence Interval. Analysis of Paired Data. Inferences Concerning a Difference between Population Proportions. Inferences Concerning Two Population Variances. 10. THE ANALYSIS OF VARIANCE. Single-Factor ANOVA. Multiple Comparisons in ANOVA. More on Single-Factor ANOVA. 11. MULTIFACTOR ANALYSIS OF VARIANCE. Two-Factor ANOVA with Kij = 1. Two-Factor ANOVA with Kij > 1. Three-Factor ANOVA. 2p Factorial Experiments. 12. SIMPLE LINEAR REGRESSION AND CORRELATION. The Simple Linear Regression Model. Estimating Model Parameters. Inferences About the Slope Parameter β1. Inferences Concerning µY•x* and the Prediction of Future Y Values. Correlation. 13. NONLINEAR AND MULTIPLE REGRESSION. Assessing Model Adequacy. Regression with Transformed Variables. Polynomial Regression. Multiple Regression Analysis. Other Issues in Multiple Regression. 14. GOODNESS-OF-FIT TESTS AND CATEGORICAL DATA ANALYSIS. Goodness-of-Fit Tests When Category Probabilities Are Completely Specified. Goodness-of-Fit Tests for Composite Hypotheses. Two-Way Contingency Tables 15. DISTRIBUTION-FREE PROCEDURES. The Wilcoxon Signed-Rank Test. The Wilcoxon Rank-Sum Test. Distribution-Free Confidence Intervals. Distribution-Free ANOVA. 16. QUALITY CONTROL METHODS. General Comments on Control Charts. Control Charts for Process Location. Control Charts for Process Variation. Control Charts for Attributes. CUSUM Procedures. Acceptance Sampling.
Summary: Put statistical theories into practice with PROBABILITY AND STATISTICS FOR ENGINEERING AND THE SCIENCES, 9E, METRIC EDITION. Always a market favorite, this calculus-based text offers a comprehensive introduction to probability and statistics while demonstrating how professionals apply concepts, models, and methodologies in today’s engineering and scientific careers. Jay Devore, an award-winning professor and internationally recognized author and statistician, stresses lively examples and engineering activities to drive home the numbers without exhaustive mathematical development and derivations. Many examples, practice problems, sample tests, and simulations based on real data and issues help you build a more intuitive connection to the material. A proven and accurate text, PROBABILITY AND STATISTICS FOR ENGINEERING AND THE SCIENCES, 9E, METRIC EDITION also includes graphics and screen shots from SAS®, MINITAB®, and Java™ Applets to give you a solid perspective of statistics in action.
List(s) this item appears in: New Arrivals- September 1st to 30th 2022
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1. OVERVIEW AND DESCRIPTIVE STATISTICS.

Populations, Samples, and Processes. Pictorial and Tabular Methods in Descriptive Statistics. Measures of Location. Measures of Variability.

2. PROBABILITY.

Sample Spaces and Events. Axioms, Interpretations, and Properties of Probability.

Counting Techniques. Conditional Probability. Independence.

3. DISCRETE RANDOM VARIABLES AND PROBABILITY DISTRIBUTIONS.

Random Variables. Probability Distributions for Discrete Random Variables.

Expected Values. The Binomial Probability Distribution. Hypergeometric and Negative Binomial Distributions. The Poisson Probability Distribution.

4. CONTINUOUS RANDOM VARIABLES AND PROBABILITY DISTRIBUTIONS.

Probability Density Functions. Cumulative Distribution Functions and Expected Values. The Normal Distribution. The Exponential and Gamma Distributions. Other Continuous Distributions. Probability Plots.

5. JOINT PROBABILITY DISTRIBUTIONS AND RANDOM SAMPLES.

Jointly Distributed Random Variables. Expected Values, Covariance, and Correlation.

Statistics and Their Distributions. The Distribution of the Sample Mean. The Distribution of a Linear Combination.

6. POINT ESTIMATION.

Some General Concepts of Point Estimation. Methods of Point Estimation.

7. STATISTICAL INTERVALS BASED ON A SINGLE SAMPLE.

Basic Properties of Confidence Intervals. Large-Sample Confidence Intervals for a Population Mean and Proportion. Intervals Based on a Normal Population Distribution.

Confidence Intervals for the Variance and Standard Deviation of a Normal Population.

8. TESTS OF HYPOTHESIS BASED ON A SINGLE SAMPLE.

Hypotheses and Test Procedures. z Tests for Hypotheses About a Population Mean.

The One-Sample t Test. Tests Concerning a Population Proportion. Further Aspects of Hypothesis Testing.

9. INFERENCES BASED ON TWO SAMPLES.

z Tests and Confidence Intervals for a Difference between Two Population Means.

The Two-Sample t Test and Confidence Interval. Analysis of Paired Data. Inferences Concerning a Difference between Population Proportions. Inferences Concerning Two Population Variances.

10. THE ANALYSIS OF VARIANCE.

Single-Factor ANOVA. Multiple Comparisons in ANOVA. More on Single-Factor ANOVA.

11. MULTIFACTOR ANALYSIS OF VARIANCE.

Two-Factor ANOVA with Kij = 1. Two-Factor ANOVA with Kij > 1. Three-Factor ANOVA. 2p Factorial Experiments.

12. SIMPLE LINEAR REGRESSION AND CORRELATION.

The Simple Linear Regression Model. Estimating Model Parameters. Inferences About the Slope Parameter β1. Inferences Concerning µY•x* and the Prediction of Future Y Values. Correlation.

13. NONLINEAR AND MULTIPLE REGRESSION.

Assessing Model Adequacy. Regression with Transformed Variables. Polynomial Regression. Multiple Regression Analysis. Other Issues in Multiple Regression.

14. GOODNESS-OF-FIT TESTS AND CATEGORICAL DATA ANALYSIS.

Goodness-of-Fit Tests When Category Probabilities Are Completely Specified. Goodness-of-Fit Tests for Composite Hypotheses. Two-Way Contingency Tables

15. DISTRIBUTION-FREE PROCEDURES.

The Wilcoxon Signed-Rank Test. The Wilcoxon Rank-Sum Test. Distribution-Free Confidence Intervals. Distribution-Free ANOVA.

16. QUALITY CONTROL METHODS.

General Comments on Control Charts. Control Charts for Process Location. Control Charts for Process Variation. Control Charts for Attributes. CUSUM Procedures.

Acceptance Sampling.

Put statistical theories into practice with PROBABILITY AND STATISTICS FOR ENGINEERING AND THE SCIENCES, 9E, METRIC EDITION. Always a market favorite, this calculus-based text offers a comprehensive introduction to probability and statistics while demonstrating how professionals apply concepts, models, and methodologies in today’s engineering and scientific careers. Jay Devore, an award-winning professor and internationally recognized author and statistician, stresses lively examples and engineering activities to drive home the numbers without exhaustive mathematical development and derivations. Many examples, practice problems, sample tests, and simulations based on real data and issues help you build a more intuitive connection to the material. A proven and accurate text, PROBABILITY AND STATISTICS FOR ENGINEERING AND THE SCIENCES, 9E, METRIC EDITION also includes graphics and screen shots from SAS®, MINITAB®, and Java™ Applets to give you a solid perspective of statistics in action.

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