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Table of Contents
Chapter 1: Fundamentals
Chapter 2: Sample Statistics are NOT Parameters
Chapter 3: Confidence
Chapter 4: Multiplicity and Multiple Comparisons
Chapter 5: Power and the Myth of Sample Size Determination
Chapter 6: Regression and Model Fitting with Collinearity
Chapter 7: Overparameterization
Chapter 8: Ignoring Error Control Factors and Experimental Design
Chapter 9: Generalized Linear Models
Chapter 10: Mixed Models and Variance Components
Chapter 11: Models, Models Everywhere...Model Selection
Chapter 12: Bayesian Analyses
Chapter 13: The Acceptance Sampling Game
Chapter 14: Nonparametric Statistics
A Strange Name
Chapter 15: Autocorrelated Data and Dynamic Systems
Chapter 16: Multivariate Analysis and Classification
Chapter 17: Time-to-Event: Survival and Life Testing
Index.
Chapter 2: Sample Statistics are NOT Parameters
Chapter 3: Confidence
Chapter 4: Multiplicity and Multiple Comparisons
Chapter 5: Power and the Myth of Sample Size Determination
Chapter 6: Regression and Model Fitting with Collinearity
Chapter 7: Overparameterization
Chapter 8: Ignoring Error Control Factors and Experimental Design
Chapter 9: Generalized Linear Models
Chapter 10: Mixed Models and Variance Components
Chapter 11: Models, Models Everywhere...Model Selection
Chapter 12: Bayesian Analyses
Chapter 13: The Acceptance Sampling Game
Chapter 14: Nonparametric Statistics
A Strange Name
Chapter 15: Autocorrelated Data and Dynamic Systems
Chapter 16: Multivariate Analysis and Classification
Chapter 17: Time-to-Event: Survival and Life Testing
Index.