Make statistics practical for engineering students in any specialty with PROBABILITY AND STATISTICS FOR ENGINEERING AND THE SCIENCES, 9E, INTERNATIONAL METRIC EDITION. Always a market leader, this calculus-based text offers a comprehensive introduction to probability and statistics while demonstrating how professionals put concepts, models, and methodologies to work in today’s 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 overly rigorous mathematical development and derivations. A variety of examples, practice problems, sample tests, and simulations based on real data and issues helps students intuitively understand the material. Proven and accurate, PROBABILITY AND STATISTICS FOR ENGINEERING AND THE SCIENCES, 9E, INTERNATIONAL METRIC EDITION also includes graphics and screen shots from SAS®, MINITAB®, and Java™ Applets to give students a solid perspective of statistics in action.

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
11. 4 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.

Make statistics practical for engineering students in any specialty with PROBABILITY AND STATISTICS FOR ENGINEERING AND THE SCIENCES, 9E, INTERNATIONAL METRIC EDITION. Always a market leader, this calculus-based text offers a comprehensive introduction to probability and statistics while demonstrating how professionals put concepts, models, and methodologies to work in today’s 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 overly rigorous mathematical development and derivations. A variety of examples, practice problems, sample tests, and simulations based on real data and issues helps students intuitively understand the material. Proven and accurate, PROBABILITY AND STATISTICS FOR ENGINEERING AND THE SCIENCES, 9E, INTERNATIONAL METRIC EDITION also includes graphics and screen shots from SAS®, MINITAB®, and Java™ Applets to give students a solid perspective of statistics in action. Authentic Data: Multiple new examples and exercises based on real data or actual problems give students practice with statistics for the modern era. Practical Probability: Examples and exercises in chapters 2 through 5 are now based on information from published sources, helping to link the concepts to contemporary issues in the workplace and at actual companies. Clearer Narratives: Polished for even better clarity, chapters focus on delivering a deep, intuitive understanding of the concepts, instead of the purely theoretical approach favored by other texts. Helpful Study Aids: Sample exams and a glossary of symbols and acronyms give students the experience and confidence they need to master concepts and ace exams. Enhanced WebAssign®: Exclusively from Cengage Learning, Enhanced WebAssign® lets you provide students with exercises from the text, multimedia tutorial support, and immediate feedback on automatically graded assignments. Key Focal Points: The author emphasizes the critical role that variation plays in statistics, including the nature of variation in the slope estimate in simple linear regression, and includes a detailed description of pooled t procedures for analysis. Sampling Simulations: "Simulation Experiments" in the text help students understand sampling distributions and the insights to gain from them, particularly when derivations are too complex to carry out. Computer Focus: An abundance of computer output from SAS® and MINITAB® supports student understanding of ANOVA and regression, while Java™ Applets specifically designed for this calculus-based text demonstrate statistics visually.