Minimax Solutions in Sampling from Finite Populations 1: Decision Theoretic Foundations in Survey Sampling 1.1 General Definitions in Survey Sampling 1.2 Examples of Sampling Strategies 1.3 Classes of Strategies 1.4 Admissible Strategies 1.5 Superpopulation Models and Blu Predictors 1.6 Bayes Estimators 1.7 Minimax Strategies 1.8 A Modified Minimax Rule 1.9 Conditional Minimax Rules 1.10 Supplements 2: Minimax Solutions in Permutation Invariant Parameter Spaces 2.1 The Permutation Model 2.2 Supplements and Generalizations 3: The Cuboid as Parameter Space 3.1 The Scott Smith Solution 3.2 Lover Bounds 3.3 Some Special Cases 3.4 Representative Minimax Solutions 3.5 Unbiased Minimax Solutions 3.6 Conditional Minimax Estimators 4: The HH Space as Parameter Space 4.1 HT Strategy Versus HH Strategy 4.2 Conditions for a Gain in Efficiency 4.3 Minimax Solutions Using the HT Estimator 4.4 Modified Minimax Solutions Using the HT Estimator 4.5 Minimax Solutions in General Classes of Strategies 5: The Generalized HH Space as Parameter Space 5.1 Determination of the Relevant Parameter Space 5.2 A Modified Minimax Estimator 5.3 Conditional Minimax Estimators 5.4 Examples 5.5 The Blu Property of the Modified and Conditional Minimax Estimator 5.6 The Modified and Conditional Estimator as Bayes Estimator 5.7 Sampling Designs With Constant Risk List of Notation.