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

1 Cover

2 PrefaceAUDIENCE 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 Theory 5.10 A Case Study 5.11 Using JMP Review Practice Problems Note Chapter 6: Distribution of Functions of Random Variables Topics Covered Learning Outcomes 6.1 Introduction 6.2 Distribution Functions of Two Random Variables 6.3 Extension to Several Random Variables 6.4 The Moment‐Generating Function Revisited Review Practice Problems Chapter 7: Sampling Distributions Topics Covered Learning Outcomes 7.1 Random Sampling 7.2 The Sampling Distribution of the Sample Mean 7.3 Sampling from a Normal Population 7.4 Order Statistics 7.5 Using JMP Review Practice Problems Chapter 8: Estimation of Population Parameters Topics Covered Learning Outcomes 8.1 Introduction 8.2 Point Estimators for the Population Mean and Variance 8.3 Interval Estimators for the Mean of a Normal Population 8.4 Interval Estimators for The Difference of Means of Two Normal Populations 8.5 Interval Estimators for the Variance of a Normal Population 8.6 Interval Estimator for the Ratio of Variances of Two Normal Populations 8.7 Point and Interval Estimators for the Parameters of Binomial Populations 8.8 Determination of Sample Size 8.9 Some Supplemental Information 8.10 A Case Study 8.11 Using JMP Review Practice Problems Note Chapter 9: Hypothesis Testing Topics Covered Learning Outcomes 9.1 Introduction 9.2 Basic Concepts of Testing a Statistical Hypothesis 9.3 Tests Concerning the Mean of a Normal Population Having Known Variance 9.4 Tests Concerning the Mean of a Normal Population Having Unknown Variance 9.5 Large Sample Theory 9.6 Tests Concerning the Difference of Means of Two Populations Having Distributions with Known Variances 9.7 Tests Concerning the Difference of Means of Two Populations Having Normal Distributions with Unknown Variances 9.8 Testing Population Proportions 9.9 Tests Concerning the Variance of a Normal Population 9.10 Tests Concerning the Ratio of Variances of Two Normal Populations 9.11 Testing of Statistical Hypotheses using Confidence Intervals 9.12 Sequential Tests of Hypotheses 9.13 Case Studies 9.14 Using JMP Review Practice Problems Chapter 10: Elements of Reliability Theory Topics Covered Learning Outcomes 10.1 The Reliability Function 10.2 Estimation: Exponential Distribution 10.3 Hypothesis Testing: Exponential Distribution 10.4 Estimation: Weibull Distribution 10.5 Case Studies 10.6 Using JMP Review Practice Problems Notes Chapter 11: On Data Mining Topics Covered Learning Outcomes 11.1 Introduction 11.2 What is Data Mining? 11.3 Data Reduction 11.4 Data Visualization 11.5 Data Preparation 11.6 Classification 11.7 Decision Trees 11.8 Case Studies 11.9 Using JMP Review Practice Problems Notes Chapter 12: Cluster Analysis Topics Covered Learning Outcomes 12.1 Introduction 12.2 Similarity Measures 12.3 Hierarchical Clustering Methods 12.4 Nonhierarchical Clustering Methods 12.5 Density‐Based Clustering 12.6 Model‐Based Clustering 12.7 A Case Study 12.8 Using JMP Review Practice Problems Notes Chapter 13: Analysis of Categorical Data Topics Covered Learning Outcomes 13.1 Introduction 13.2 The Chi‐Square Goodness‐of‐Fit Test 13.3 Contingency Tables 13.4 Chi‐Square Test for Homogeneity 13.5 Comments on the Distribution of the Lack‐of‐Fit Statistics 13.6 Case Studies Using JMP Review Practice Problems Note Chapter 14: Nonparametric Tests Topics Covered Learning Outcomes 14.1 Introduction 14.2 The Sign Test 14.3 Mann–Whitney (Wilcoxon) Test for Two Samples 14.4 Runs Test 14.5 Spearman Rank Correlation 14.6 Using JMP Review Practice Problems Chapter 15: Simple Linear Regression Analysis Topics Covered Learning Outcomes 15.1 Introduction 15.2 Fitting the Simple Linear Regression Model 15.3 Unbiased Estimator of σ2 15.4 Further Inferences Concerning Regression Coefficients (, ),, and 15.5 Tests of Hypotheses for and 15.6 Analysis of Variance Approach to Simple Linear Regression Analysis 15.7 Residual Analysis 15.8 Transformations 15.9 Inference About ρ 15.10 A Case Study 15.11 Using JMP Review Practice Problems Note Chapter 16: Multiple Linear Regression Analysis Topics Covered Learning Outcomes 16.1 Introduction 16.2 Multiple Linear Regression Models 16.3 Estimation of Regression Coefficients 16.4 Multiple Linear Regression Model Using Quantitative and Qualitative Predictor Variables 16.5 Standardized Regression Coefficients 16.6 Building Regression Type Prediction Models 16.7 Residual Analysis and Certain Criteria for Model Selection 16.8 Logistic Regression 16.9 Case Studies 16.10 Using JMP Review Practice Problems Notes Chapter 17: Analysis of Variance Topics Covered Learning Outcomes 17.1 Introduction 17.2 The Design Models 17.3 One‐Way Experimental Layouts 17.4 Randomized Complete Block (RCB) Designs 17.5 Two‐Way Experimental Layouts 17.6 Latin Square Designs 17.7 Random‐Effects and Mixed‐Effects Models 17.8 A Case Study 17.9 Using JMP Review Practice Problems Note Chapter 18: The 2 kFactorial Designs Topics Covered Learning Outcomes 18.1 Introduction 18.2 The Factorial Designs 18.3 The 2 Factorial Designs 18.4 Unreplicated 2 Factorial Designs 18.5 Blocking in the 2 Factorial Design 18.6 The 2 kFractional Factorial Designs 18.7 Case Studies 18.8 Using JMP Review Practice Problems Notes Chapter 19: Response Surfaces Topics Covered Learning Outcomes 19.1 Introduction 19.2 First‐Order Designs 19.3 Second‐Order Designs 19.4 Determination of Optimum or Near‐Optimum Point 19.5 Anova Table for a Second‐Order Model 19.6 Case Studies 19.7 Using JMP Review Practice Problems Note Chapter 20: Statistical Quality Control—Phase I Control Charts Topics Covered Learning Outcomes Chapter 21: Statistical Quality Control—Phase II Control Charts Topics Covered Learning Outcomes Note