Probability and Statistics for Engineers 9th Edition by Richard Johnson, Irwin Miller, John Freund – Ebook PDF Instant Download/Delivery: 1292176017, 9781292176017
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ISBN 10: 1292176017
ISBN 13: 9781292176017
Author: Richard Johnson, Irwin Miller, John Freund
The full text downloaded to your computer With eBooks you can: search for key concepts, words and phrases make highlights and notes as you study share your notes with friends eBooks are downloaded to your computer and accessible either offline through the Bookshelf (available as a free download), available online and also via the iPad and Android apps. Upon purchase, you’ll gain instant access to this eBook. Time limit The eBooks products do not have an expiry date. You will continue to access your digital ebook products whilst you have your Bookshelf installed. For an introductory or one or two semester courses in Probability and Statistics or Applied Statistics for engineering, physical science, and mathematics students. An Applications-Focused Introduction to Probability and Statistics Miller & Freund’s Probability and Statistics for Engineers is rich in exercises and examples, and explores both elementary probability and basic statistics, with an emphasis on engineering and science applications. Much of the data has been collected from the author’s own consulting experience and from discussions with scientists and engineers about the use of statistics in their fields. In later chapters, the text emphasises designed experiments, especially two-level factorial design. The Ninth Edition includes several new datasets and examples showing application of statistics in scientific investigations, familiarising students with the latest methods, and readying them to become real-world engineers and scientists.
Probability and Statistics for Engineers 9th Table of contents:
Chapter 1 Introduction
1.1 Why Study Statistics?
1.2 Modern Statistics
1.3 Statistics and Engineering
1.4 The Role of the Scientist and Engineer in Quality Improvement
1.5 A Case Study: Visually Inspecting Data to Improve Product Quality
1.6 Two Basic Concepts—Population and Sample
Review Exercises
Key Terms
Chapter 2 Organization and Description of Data
2.1 Pareto Diagrams and Dot Diagrams
2.2 Frequency Distributions
2.3 Graphs of Frequency Distributions
2.4 Stem-and-Leaf Displays
2.5 Descriptive Measures
2.6 Quartiles and Percentiles
2.7 The Calculation of x and s
2.8 A Case Study: Problems with Aggregating Data
Review Exercises
Key Terms
Chapter 3 Probability
3.1 Sample Spaces and Events
3.2 Counting
3.3 Probability
3.4 The Axioms of Probability
3.5 Some Elementary Theorems
3.6 Conditional Probability
3.7 Bayes’ Theorem
Review Exercises
Key Terms
Chapter 4 Probability Distributions
4.1 Random Variables
4.2 The Binomial Distribution
4.3 The Hypergeometric Distribution
4.4 The Mean and the Variance of a Probability Distribution
4.5 Chebyshev’s Theorem
4.6 The Poisson Distribution and Rare Events
4.7 Poisson Processes
4.8 The Geometric and Negative Binomial Distribution
4.9 The Multinomial Distribution
4.10 Simulation
Review Exercises
Key Terms
Chapter 5 Probability Densities
5.1 Continuous Random Variables
5.2 The Normal Distribution
5.3 The Normal Approximation to the Binomial Distribution
5.4 Other Probability Densities
5.5 The Uniform Distribution
5.6 The Log-Normal Distribution
5.7 The Gamma Distribution
5.8 The Beta Distribution
5.9 TheWeibull Distribution
5.10 Joint Distributions—Discrete and Continuous
5.11 Moment Generating Functions
5.12 Checking If the Data Are Normal
5.13 Transforming Observations to Near Normality
5.14 Simulation
Review Exercises
Key Terms
Chapter 6 Sampling Distributions
6.1 Populations and Samples
6.2 The Sampling Distribution of the Mean (σ known)
6.3 The Sampling Distribution of the Mean (σ unknown)
6.4 The Sampling Distribution of the Variance
6.5 Representations of the Normal Theory Distributions
6.6 The Moment Generating Function Method to Obtain Distributions
6.7 Transformation Methods to Obtain Distributions
Review Exercises
Key Terms
Chapter 7 Inferences Concerning a Mean
7.1 Statistical Approaches to Making Generalizations
7.2 Point Estimation
7.3 Interval Estimation
7.4 Maximum Likelihood Estimation
7.5 Tests of Hypotheses
7.6 Null Hypotheses and Tests of Hypotheses
7.7 Hypotheses Concerning One Mean
7.8 The Relation between Tests and Confidence Intervals
7.9 Power, Sample Size, and Operating Characteristic Curves
Review Exercises
Key Terms
Chapter 8 Comparing Two Treatments
8.1 Experimental Designs for Comparing Two Treatments
8.2 Comparisons—Two Independent Large Samples
8.3 Comparisons—Two Independent Small Samples
8.4 Matched Pairs Comparisons
8.5 Design Issues—Randomization and Pairing
Review Exercises
Key Terms
Chapter 9 Inferences Concerning Variances
9.1 The Estimation of Variances
9.2 Hypotheses Concerning One Variance
9.3 Hypotheses Concerning Two Variances
Review Exercises
Key Terms
Chapter 10 Inferences Concerning Proportions
10.1 Estimation of Proportions
10.2 Hypotheses Concerning One Proportion
10.3 Hypotheses Concerning Several Proportions
10.4 Analysis of r x c Tables
10.5 Goodness of Fit
Review Exercises
Key Terms
Chapter 11 Regression Analysis
11.1 The Method of Least Squares
11.2 Inferences Based on the Least Squares Estimators
11.3 Curvilinear Regression
11.4 Multiple Regression
11.5 Checking the Adequacy of the Model
11.6 Correlation
11.7 Multiple Linear Regression (Matrix Notation)
Review Exercises
Key Terms
Chapter 12 Analysis of Variance
12.1 Some General Principles
12.2 Completely Randomized Designs
12.3 Randomized-Block Designs
12.4 Multiple Comparisons
12.5 Analysis of Covariance
Review Exercises
Key Terms
Chapter 13 Factorial Experimentation
13.1 Two-Factor Experiments
13.2 Multifactor Experiments
13.3 The Graphic Presentation of 22 and 23 Experiments
13.4 Response Surface Analysis
Review Exercises
Key Terms
Chapter 14 Nonparametric Tests
14.1 Introduction
14.2 The Sign Test
14.3 Rank-Sum Tests
14.4 Correlation Based on Ranks
14.5 Tests of Randomness
14.6 The Kolmogorov-Smirnov and Anderson-Darling Tests
Review Exercises
Key Terms
Chapter 15 The Statistical Content of Quality-Improvement Programs
15.1 Quality-Improvement Programs
15.2 Starting a Quality-Improvement Program
15.3 Experimental Designs for Quality
15.4 Quality Control
15.5 Control Charts for Measurements
15.6 Control Charts for Attributes
15.7 Tolerance Limits
Review Exercises
Key Terms
Chapter 16 Application to Reliability and Life Testing
16.1 Reliability
16.2 Failure-Time Distribution
16.3 The Exponential Model in Life Testing
16.4 The Weibull Model in Life Testing
Review Exercises
Key Terms
Appendix A Bibliography
Appendix B Statistical Tables
Appendix C Using the R Software Program
Introduction to R
Entering Data
Arithmetic Operations
Descriptive Statistics
Probability Distributions
Normal Probability Calculations
Sampling Distributions
Confidence Intervals and Tests of Means
Inference about Proportions
Regression
One-Way Analysis of Variance (ANOVA)
Appendix D Answers to Odd-Numbered Exercises
Index
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Tags: Richard Johnson, Irwin Miller, John Freund, Probability and Statistics


