Probability and Statistics for Engineering and the Sciences 9th Edition by Jay Devore ISBN 9781337094269 1337094269

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ISBN 10: 1337094269
ISBN 13: 9781337094269
Author: Jay Devore

Probability and Statistics for Engineering and the Sciences 9th Edition Table of contents:

Ch 1: Overview and Descriptive Statistics
Introduction
1.1: Populations, Samples, and Processes
1.2: Pictorial and Tabular Methods in Descriptive Statistics
1.3: Measures of Location
1.4: Measures of Variability
Supplementary Exercises (62-83)
Bibliography
Ch 2: Probability
Introduction
2.1: Sample Spaces and Events
2.2: Axioms, Interpretations, and Properties of Probability
2.3: Counting Techniques
2.4: Conditional Probability
2.5: Independence
Supplementary Exercises (90-114)
Bibliography
Ch 3: Discrete Random Variables and Probability Distributions
Introduction
3.1: Random Variables
3.2: Probability Distributions for Discrete Random Variables
3.3: Expected Values
3.4: The Binomial Probability Distribution
3.5: Hypergeometric and Negative Binomial Distributions
3.6: The Poisson Probability Distribution
Supplementary Exercises (94-122)
Bibliography
Ch 4: Continuous Random Variables and Probability Distributions
Introduction
4.1: Probability Density Functions
4.2: Cumulative Distribution Functions and Expected Values
4.3: The Normal Distribution
4.4: The Exponential and Gamma Distributions
4.5: Other Continuous Distributions
4.6: Probability Plots
Supplementary Exercises (98-128)
Bibliography
Ch 5: Joint Probability Distributions and Random Samples
Introduction
5.1: Jointly Distributed Random Variables
5.2: Expected Values, Covariance, and Correlation
5.3: Statistics and Their Distributions
5.4: The Distribution of the Sample Mean
5.5: The Distribution of a Linear Combination
Supplementary Exercises (75-96)
Bibliography
Ch 6: Point Estimation
Introduction
6.1: Some General Concepts of Point Estimation
6.2: Methods of Point Estimation
Supplementary Exercises (31-38)
Bibliography
Ch 7: Statistical Intervals Based on a Single Sample
Introduction
7.1: Basic Properties of Confidence Intervals
7.2: Large-Sample Confidence Intervals for a Population Mean and Proportion
7.3: Intervals Based on a Normal Population Distribution
7.4: Confidence Intervals for the Variance and Standard Deviation of a Normal Population
Supplementary Exercises (47-62)
Bibliography
Ch 8: Tests of Hypotheses Based on a Single Sample
Introduction
8.1: Hypotheses and Test Procedures
8.2: z Tests for Hypotheses about a Population Mean
8.3: The One-Sample t Test
8.4: Tests Concerning a Population Proportion
8.5: Further Aspects of Hypothesis Testing
Supplementary Exercises (57-80)
Bibliography
Ch 9: Inferences Based on Two Samples
Introduction
9.1: z Tests and Confidence Intervals for a Difference between Two Population Means
9.2: The Two-Sample t Test and Confidence Interval
9.3: Analysis of Paired Data
9.4: Inferences Concerning a Difference between Population Proportions
9.5: Inferences Concerning Two Population Variances
Supplementary Exercises (67-95)
Bibliography
Ch 10: The Analysis of Variance
Introduction
10.1: Single-Factor ANOVA
10.2: Multiple Comparisons in ANOVA
10.3: More on Single-Factor ANOVA
Supplementary Exercises (35-46)
Bibliography
Ch 11: Multifactor Analysis of Variance
Introduction
11.1: Two-Factor ANOVA with Kij = 1
11.2: Two-Factor ANOVA with Kij > 1
11.3: Three-Factor ANOVA
11.4: 2p Factorial Experiments
Supplementary Exercises (50-61)
Bibliography
Ch 12: Simple Linear Regression and Correlation
Introduction
12.1: The Simple Linear Regression Model
12.2: Estimating Model Parameters
12.3: Inferences about the Slope Parameter B1
12.4: Inferences Concerning uY . x* and the Prediction of Future Y Values
12.5: Correlation
Supplementary Exercises (68-87)
Bibliography
Ch 13: Nonlinear and Multiple Regression
Introduction
13.1: Assessing Model Adequacy
13.2: Regression with Transformed Variables
13.3: Polynomial Regression
13.4: Multiple Regression Analysis
13.5: Other Issues in Multiple Regression
Supplementary Exercises (65-83)
Bibliography
Ch 14: Goodness-of-Fit Tests and Categorical Data Analysis
Introduction
14.1: Goodness-of-Fit Tests When Category Probabilities are Completely Specified
14.2: Goodness-of-Fit Tests for Composite Hypotheses
14.3: Two-Way Contingency Tables
Supplementary Exercises (37-49)
Bibliography
Ch 15: Distribution-Free Procedures
Introduction
15.1: The Wilcoxon Signed-Rank Test
15.2: The Wilcoxon Rank-Sum Test
15.3: Distribution-Free Confidence Intervals
15.4: Distribution-Free ANOVA
Supplementary Exercises (28-36)
Bibliography
Ch 16: Quality Control Methods
Introduction
16.1: General Comments on Control Charts
16.2: Control Charts for Process Location
16.3: Control Charts for Process Variation
16.4: Control Charts for Attributes
16.5: CUSUM Procedures
16.6: Acceptance Sampling

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