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

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

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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

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