Statistics and Probability with Applications for Engineers and Scientists Using MINITAB, R and JMP. Bhisham C. Gupta

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      1  Cover

      2  Preface AUDIENCE MOTIVATION HISTORY APPROACH HALLMARK FEATURES

      3  Acknowledgments

      4  About The Companion Site

      5  Chapter 1: Introduction 1.1 Designed Experiment 1.2 A Survey 1.3 An Observational Study 1.4 A Set of Historical Data 1.5 A Brief Description of What is Covered in this Book

      6  Part I: Fundamentals of Probability and Statistics Chapter 2: Describing Data Graphically and Numerically Topics Covered Learning Outcomes 2.1 Getting Started with Statistics 2.2 Classification of Various Types of Data 2.3 Frequency Distribution Tables for Qualitative and Quantitative Data 2.4 Graphical Description of Qualitative and Quantitative Data 2.5 Numerical Measures of Quantitative Data 2.6 Numerical Measures of Grouped Data 2.7 Measures of Relative Position 2.8 Box‐Whisker Plot 2.9 Measures of Association 2.10 Case Studies 2.11 Using JMP Review Practice Problems Notes Chapter 3: Elements of Probability Topics Covered Learning Outcomes 3.1 Introduction 3.2 Random Experiments, Sample Spaces, and Events 3.3 Concepts of Probability 3.4 Techniques of Counting Sample Points 3.5 Conditional Probability 3.6 Bayes's Theorem 3.7 Introducing Random Variables Review Practice Problems Chapter 4: Discrete Random Variables and Some Important Discrete Probability Distributions Topics Covered Learning Outcomes 4.1 Graphical Descriptions of Discrete Distributions 4.2 Mean and Variance of a Discrete Random Variable 4.3 The Discrete Uniform Distribution 4.4 The Hypergeometric Distribution 4.5 The Bernoulli Distribution 4.6 The Binomial Distribution 4.7 The Multinomial Distribution 4.8 The Poisson Distribution 4.9 The Negative Binomial Distribution 4.10 Some Derivations and Proofs (Optional) 4.11 A Case Study 4.12 Using JMP Review Practice Problems Note Chapter 5: Continuous Random Variables and Some Important Continuous Probability Distributions Topics Covered Learning Outcomes 5.1 Continuous Random Variables 5.2 Mean and Variance of Continuous Random Variables 5.3 Chebyshev's Inequality 5.4 The Uniform Distribution 5.5 The Normal Distribution 5.6 Distribution of Linear Combination of Independent Normal Variables 5.7 Approximation of the Binomial and Poisson Distributions by the Normal Distribution 5.8 A Test of Normality 5.9 Probability Models Commonly used in Reliability СКАЧАТЬ