Miller and Freunds Probability and Statistics for Engineers 9th Edition by Richard Johnson, Irwin Miller, John Freund 0134435680 9780134435688

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ISBN-10 :  0134435680 

ISBN-13 :  9780134435688‎

Author: Richard A. Johnson, Irwin Miller, John E. Freund

Miller & Freund’s Probability & 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 emphasizes designed experiments, especially 2-level factorial design. The 9th Edition includes several new datasets and examples showing application of statistics in scientific investigations, familiarizing students with the latest methods, and readying them to become real-world engineers and scientists. This title is part of the Pearson Modern Classics series. Pearson Modern Classics are acclaimed titles at a value price.

Miller and Freund’s Probability and Statistics for Engineers 9th Table of contents:

Chapter 1 Introduction
Chapter Outline
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
Solution
Solution
Using a random number table to select samples
Solution
Solution
Do’s
Don’ts
Review Exercises
Key Terms
Chapter 2 Organization and Description of Data
Chapter Outline
2.1 Pareto Diagrams and Dot Diagrams
Solution
Solution
2.2 Frequency Distributions
Solution
Solution
2.3 Graphs of Frequency Distributions
Solution
Solution
Solution
2.4 Stem-and-Leaf Displays
Exercise
2.5 Descriptive Measures
Solution
Solution
Solution
Solution
Solution
Solution
2.6 Quartiles and Percentiles
Solution
Solution
Boxplots
Solution
Solution
2.7 The Calculation of x̲ and s
Solution
Solution
Exercise
2.8 A Case Study: Problems with Aggregating Data
Do’s
Don’ts
Review Exercises
Key Terms
Chapter 3 Probability
Chapter Outline
3.1 Sample Spaces and Events
Solution
Solution
Solution
3.2 Counting
Multiplication of choices
Solution
Solution
Solution
Number of permutations of n objects taken r at a time
Solution
Number of combinations of n objects taken r at a time
Solution
Solution
Solution
Exercise
3.3 Probability
Solution
Solution
Solution
3.4 The Axioms of Probability
Solution
3.5 Some Elementary Theorems
Generalization of the third axiom of probability
Solution
Rule for calculating probability of an event
Solution
General addition rule for probability
Solution
Solution
Probability rule of the complement
Solution
Exercise
3.6 Conditional Probability
Solution
Solution
General multiplication rule of probability
Solution
Special product rule of probability
Solution
Solution
Solution
Solution
Solution
Solution
Solution
3.7 Bayes’ Theorem
Rule of total probability
Bayes’ theorem
Solution
Solution
Exercise
Do’s
Don’ts
Review Exercises
Key Terms
Chapter 4 Probability Distributions
Chapter Outline
4.1 Random Variables
Solution
4.2 The Binomial Distribution
Solution
Solution
Solution
Solution
Solution
Solution
4.3 The Hypergeometric Distribution
Solution
Solution
Exercise
4.4 The Mean and the Variance of a Probability Distribution
Solution
4.5 Chebyshev’s Theorem
Chebyshev’s theorem
Solution
Solution
Exercise
4.6 The Poisson Distribution and Rare Events
Solution
The Poisson Approximation to the Binomial Distribution
Solution
Solution
4.7 Poisson Processes
Solution
Solution
4.8 The Geometric and Negative Binomial Distribution
Solution
Exercise
4.9 The Multinomial Distribution
Solution
Exercise
4.10 Simulation
Solution
Exercise
Do’s
Don’ts
Review Exercises
Key Terms
Chapter 5 Probability Densities
Chapter Outline
5.1 Continuous Random Variables
Solution
Exercise
5.2 The Normal Distribution
Solution
5.3 The Normal Approximation to the Binomial Distribution
Normal approximation to binomial distribution
Solution
Exercise
5.4 Other Probability Densities
5.5 The Uniform Distribution
5.6 The Log-Normal Distribution
Solution
5.7 The Gamma Distribution
Solution
Solution
5.8 The Beta Distribution
Solution
5.9 The Weibull Distribution
Solution
Exercise
5.10 Joint Distributions—Discrete and Continuous
Discrete Variables
Solution
Solution
Continuous Variables
Solution
Properties of Expectation
Solution
Exercise
5.11 Moment Generating Functions*
Basic properties of moment generating functions
Solution
Moment generating function of a+bX
Solution
Exercise
5.12 Checking If the Data Are Normal
Solution
5.13 Transforming Observations to Near Normality
Solution
Exercise
5.14 Simulation
Solution
Solution
Exercise
Do’s
Don’sts
Review Exercises
Summary of Distributions
Key Terms
Chapter 6 Sampling Distributions
Chapter Outline
6.1 Populations and Samples
Solution
6.2 The Sampling Distribution of the Mean (σ known)
Formulas for μX̲ and σX̲ 2
Solution
Law of large numbers
Solution
Theorem 6.3
Solution
Exercise
6.3 The Sampling Distribution of the Mean (σ unknown)
A random variable having the t distribution
Solution
6.4 The Sampling Distribution of the Variance
A random variable having the chi square distribution
Solution
A random variable having the F distribution
Solution
Solution
Exercise
6.5 Representations of the Normal Theory Distributions
Solution
Exercise
6.6 The Moment Generating Function Method to Obtain Distributions*
Moment generating function for sum of n independent random variables
Solution
Exercise
6.7 Transformation Methods to Obtain Distributions*
Distribution Function Method
Solution
Solution
Transformation Method
Density function of h(X)
Solution
Convolution formula
Solution
Convolution Formula for Discrete Random Variables
Discrete convolution formula
Solution
Exercise
Do’s
Don’ts
Review Exercises
Key Terms
Chapter 7 Inferences Concerning a Mean
Chapter Outline
7.1 Statistical Approaches to Making Generalizations
Solution
7.2 Point Estimation
Solution
Maximum Error of Estimate with High Probability
Solution
Solution
Determination of Sample Size
Solution
7.3 Interval Estimation
Solution
Solution
Solution
Exercise
7.4 Maximum Likelihood Estimation
Solution
Exercise
7.5 Tests of Hypotheses
Solution
7.6 Null Hypotheses and Tests of Hypotheses
Solution
Exercise
7.7 Hypotheses Concerning One Mean
Solution
Solution
Solution
Exercise
7.8 The Relation between Tests and Confidence Intervals
Solution
Exercise
7.9 Power, Sample Size, and Operating Characteristic Curves*
Solution
Solution
Solution
Exercise
Do’s
Don’ts
Review Exercises
Key Terms
Chapter 8 Comparing Two Treatments
Chapter Outline
8.1 Experimental Designs for Comparing Two Treatments
Solution
Solution
8.2 Comparisons—Two Independent Large Samples
Assumptions—Large Samples
Large Samples Confidence Intervals
Solution
Large Samples Tests for Differences of Means
Solution
8.3 Comparisons—Two Independent Small Samples
Additional Assumptions for Small Samples
Solution
Small Sample Sizes but Unequal Standard Deviations—Normal Populations
Solution
Exercise
8.4 Matched Pairs Comparisons
Solution
Exercise
8.5 Design Issues—Randomization and Pairing
Independent Samples Design: Randomization
Matched Pairs Design: Pairing and Randomization
Exercise
Do’s
Don’ts
Review Exercises
Key Terms
Chapter 9 Inferences Concerning Variances
Chapter Outline
9.1 The Estimation of Variances
Solution
Solution
Exercise
9.2 Hypotheses Concerning One Variance
Solution
9.3 Hypotheses Concerning Two Variances
Solution
Caution
Exercise
Do’s
Don’ts
Review Exercises
Key Terms
Chapter 10 Inferences Concerning Proportions
Chapter Outline
10.1 Estimation of Proportions
Solution
A Conservative Confidence Interval of a Proportion
Solution
A Large Sample Confidence Interval for a Proportion
Solution
Exercise
10.2 Hypotheses Concerning One Proportion
Exact Test with Conservative Significance Level
Solution
Large Sample Test of a Proportion
Solution
10.3 Hypotheses Concerning Several Proportions
Solution
Solution
Solution
Solution
Exercise
10.4 Analysis of r×c Tables
Solution
Solution
Solution
10.5 Goodness of Fit
Solution
Exercise
Do’s
Don’ts
Review Exercises
Key Terms
Chapter 11 Regression Analysis
Chapter Outline
11.1 The Method of Least Squares
Solution
Solution
Solution
Determining the Least Squares Estimators
Normal Equations for the Least Squares Estimators
Solution
11.2 Inferences Based on the Least Squares Estimators
Statistics for inferences about α and β
Solution
Exercise
11.3 Curvilinear Regression
Solution
Solution
11.4 Multiple Regression
Solution
Solution
11.5 Checking the Adequacy of the Model
Exercise
11.6 Correlation
Solution
Solution
Correlation and Regression
Solution
Correlation and Causation
Inference about the Correlation Coefficient (Normal Populations)
Solution
Solution
(Optional) The Bivariate Normal Distribution and the Straight-Line Regression Model
Exercise
11.7 Multiple Linear Regression (Matrix Notation)
Solution
Solution
Solution
Do’s
Don’ts
Review Exercises
Key Terms
Chapter 12 Analysis of Variance
Chapter Outline
12.1 Some General Principles
12.2 Completely Randomized Designs
Identity for one-way analysis of variance
Solution
Alternative Calculation of Sums of Squares
Solution
Exercises
One-Way Analysis of Variance
12.3 Randomized-Block Designs
Identity for analysis of two-way classification
Solution
Solution
Alternative Calculation of Sums of Squares
Solution
12.4 Multiple Comparisons
Solution
Solution
Exercises
12.5 Analysis of Covariance
Solution
Exercises
Do’s
Don’ts
Review Exercises
Key Terms
Chapter 13 Factorial Experimentation
Chapter Outline
13.1 Two-Factor Experiments
Decomposition of sum of squares for two-way factorial design
Solution
Solution
13.2 Multifactor Experiments
Solution
Exercise
13.3 The Graphic Presentation of 22 and 23 Experiments
22 Design
Estimates of effects
Confidence intervals for the effects
Model Assumptions
23 Design
Estimates of effects
Confidence intervals for the effects
Model Assumptions
Blocking in a 23 design
Exercise
13.4 Response Surface Analysis
Solution
Exercise
Do’s
Don’ts
Review Exercises
Key Terms
Chapter 14 Nonparametric Tests
Chapter Outline
14.1 Introduction
14.2 The Sign Test
Solutions
Solutions
14.3 Rank-Sum Tests
Solutions
Solutions
14.4 Correlation Based on Ranks
Solutions
Exercise
14.5 Tests of Randomness
Solutions
Solutions
14.6 The Kolmogorov-Smirnov and Anderson-Darling Tests
Solutions
Solutions
Exercise
Do’s
Don’ts
Review Exercises
Key Terms
Chapter 15 The Statistical Content of Quality-Improvement Programs
Chapter Outline
15.1 Quality-Improvement Programs
15.2 Starting a Quality-Improvement Program
15.3 Experimental Designs for Quality
Solutions
15.4 Quality Control
Solutions
15.5 Control Charts for Measurements
15.6 Control Charts for Attributes
Exercises
15.7 Tolerance Limits
Solutions
Solutions
Exercise
Do’s
Don’ts
Review Exercises
Key Terms
15.8 Acceptance Sampling
Exercise
Chapter 16 Application to Reliability and Life Testing
Chapter Outline
16.1 Reliability
Solutions
Solutions
16.2 Failure-Time Distribution
Exercises
16.3 The Exponential Model in Life Testing
Solutions
Solution
16.4 The Weibull Model in Life Testing
Exercises
Do’s
Don’ts
Review Exercises

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